Infrastructure monitoring tools can confirm degradation, and application performance monitoring can show response times. But neither explains how orchestrated workflows behaved under pressure: how dependencies interacted, where contention formed or why service-level agreement (SLA) risk accumulated.

As orchestration expands across SAP landscapes, cloud-native services, data pipelines and external APIs, that blind spot becomes harder to ignore. Automation platforms generate telemetry continuously, so the challenge isn’t collecting data, but preserving its context.

Without that context, your teams may find themselves working backwards, which often means piecing together timelines, comparing dashboards and explaining outcomes after the fact. With it, they gain something closer to a panoramic view that makes risk visible earlier and turns automation data into a feedback loop they can actually use.

Redwood Software addresses this directly with Redwood Insights for RunMyJobs, embedding observability into the orchestration layer itself — not bolting it on.

Evolving from system signals to orchestration intelligence

Observability platforms were built around applications and infrastructure. They excel at collecting distributed telemetry and tracking system performance.

Enterprise orchestration introduces a different dimension of complexity:

• Cross-platform workflows with layered dependencies
• SLA-bound business processes such as financial close or order-to-cash
• High-volume batch and event-driven workloads
• Deep SAP integration across ERP and SAP Business Technology Platform (BTP)

When an issue emerges, teams often pivot between different monitoring tools, logs and dashboards to reconstruct the sequence of events. The signals are there, but the intent is missing. Correlation must be manual. Thus, mean time to resolution (MTTR) grows because the orchestration logic — how workflows were designed to behave — lives somewhere else (e.g., in RunMyJobs by Redwood).

Redwood Insights closes that gap by keeping execution data tied to workflow relationships, orchestration intent and historical context. Instead of reviewing isolated metrics, you can see how workflows behaved as connected systems.

What changes first is the quality of investigation. Rather than chasing symptoms across tools, engineers start with the workflow itself. Root causes can surface faster and patterns are easier to spot. Less energy has to be expended for reacting and preventing the same issues from repeating.

Native operational visibility in RunMyJobs

Redwood Insights is available to every RunMyJobs SaaS customer, offering:

• Pre-built dashboards that surface execution trends, runtime variance and failure clustering across environments
• Bottleneck visibility that prevents escalation into SLA breaches 
• Immutable audit visibility and summarized execution history for administrators — without exporting data to external tools
• A high-level dashboard for engineers to move directly into specific workflow executions, eliminating platform switching or manual correlation

The views above create a shared operational baseline. Your automation health becomes easier to understand, explain and improve upon, no matter if your goal is faster triage, cleaner audits or shorter processing windows.

The impact shows up in measurable ways:

• Root causes take less time to uncover
• Mean time to repair drops
• Recurring bottlenecks surface earlier
• System behavior becomes more predictable across distributed environments

Orchestration gets its own observable voice.

Redwood Insights Premium: Extending visibility to enterprise scale

With automation becoming increasingly central to business operations, observability needs to support more than incident response.

Redwood Insights Premium, introduced in RunMyJobs 2026.1, builds on the native foundation with:

• A no-code dashboard designer for customized views
• Easy sharing of custom dashboards across the business
• 15 months of historical data retention

For many organizations, this marks a shift from short-term visibility to longer-term performance management, moving from “what just happened” to “what keeps happening, and why.” 

Custom dashboards and KPI alignment

Different stakeholders require different perspectives. For example, auditors look for records of changes made to automation environments. And Finance leaders care about SLA adherence and process completion risk.

Redwood Insights Premium allows IT to define custom dashboards for tracking KPIs tied directly to orchestrated workflows. Automation performance can then be measured against declared business objectives rather than generic system metrics.

Secure sharing gives process owners and domain leaders self-service access to their own views, while governance remains centralized. This ultimately changes how insights flow through the organization, because IT is no longer the default intermediary. Business teams can have direct visibility into the processes they depend on, too.

Long-term telemetry for planning and governance

Short monitoring windows are useful for resolving today’s incidents, but they don’t help much with planning.

With 15 months of historical data retention, it’s possible to:

• Benchmark year-over-year workload performance
• Identify seasonal execution patterns
• Evaluate the impact of architectural changes
• Support audit and compliance preparation with a continuous execution history

For CIOs and transformation leaders, this longer view supports more grounded ROI conversations. Decisions about scaling orchestration, modernizing SAP landscapes or optimizing cloud consumption can be based on how systems actually behave over time. Observability, therefore, becomes a planning instrument instead of merely a diagnostic tool.

Correlating automation across the broader observability ecosystem

Many enterprises already rely on multiple observability platforms. Infrastructure and application telemetry continue to flow into tools such as Splunk, Dynatrace, New Relic and AppDynamics. RunMyJobs integrates automation telemetry with these platforms, enabling teams to correlate workflow behavior with application and infrastructure performance.

For SAP-centric organizations, the out-of-the-box SAP Cloud ALM connector synchronizes RunMyJobs execution data, including status, start delays and runtime, directly into SAP Job and Automation Monitoring. Automation health becomes visible in the operational interface that SAP teams already use.

Instead of losing orchestration context as data moves between systems, it’s easy to retain a clear picture of how workflow behavior contributes to business risk.

Observability as an architectural decision

Observability is often framed as a DevOps concern. But in distributed enterprises, it’s an architectural one.

As orchestration spans SAP, cloud-native services, hybrid infrastructure and external APIs, leaders need confidence that critical workflows will remain predictable and transparent. Modernization initiatives, from SAP Cloud ERP transformations to multi-cloud adoption, depend on reliable execution.

By embedding observability, RunMyJobs creates a continuous feedback loop:

• Telemetry highlights friction
• Teams optimize workflows
• Reliability improves
• Business outcomes follow

Automation already underpins your most critical processes. With Redwood Insights and Redwood Insights Premium, it becomes fully observable — not only at the system level, but at the orchestration level where business risk actually resides.

Already a Redwood Software customer? Review all the features released in 2026.1.

Ready to democratize your data? Request a demo of RunMyJobs, including Redwood Insights Premium, and see how tailored observability changes how your teams work.

Few organizations achieve that kind of orchestration consistently, because their automation is fragmented. One team might manage batch jobs, and another might script data pipelines. A third could rely on manual interventions and shared inboxes to keep business processes moving.

The value of a Service Orchestration and Automation Platform (SOAP) lies in its ability to unify these silos and support the workflows that actually run the business. In its 2025 Critical Capabilities for SOAPs report, Gartner® outlines five Use Cases that demonstrate this value in action. Here’s how, in my interpretation, those capabilities show up in real operations across industries.

IT workload automation: Still essential

No matter how much technology evolves, the reliance on routine workloads never really goes away. Nightly ERP updates, hourly job chains and critical data movements between systems are fundamental processes that keep your business running.

But those workloads aren’t confined to a single mainframe or on-premises scheduler anymore. They span hybrid environments, connect to cloud-based APIs and carry tighter service-level agreement (SLA) expectations than ever before. The hard part isn’t the workload itself but the web of dependencies and recovery paths that stretch across different systems.

A robust SOAP solution lets you orchestrate all these elements in one place: SAP jobs, custom scripts, data movements and file transfers, for instance. You gain centralized control with distributed execution — the perfect balance for hybrid IT environments. I feel Gartner points to this as a foundational Use Case because it tests how well a platform performs under enterprise pressure — securely, reliably and with minimal manual intervention.

What this unlocks: With dependable workload automation, your IT teams can start each day with confidence that core batch processes ran cleanly and dependencies resolved in the right order. Not to mention, any failures were isolated and didn’t cause unwanted ripple effects. Your operational tone can shift from checking for surprises to reviewing a clean audit trail and planning ahead.

Workflow orchestration: Running the business, not just jobs

Behind every business outcome is a complex chain of tasks, approvals and exceptions that span multiple systems and departments. Take the month-end financial close: it happens thanks to finance systems, spreadsheets, validations and cross-departmental collaboration. Or consider onboarding a new hire. Beyond provisioning accounts, it requires scheduling training, initiating background checks and activating access across multiple systems.

With a SOAP platform, these workflows can be orchestrated end to end. Instead of managing each step separately, you create a unified process that flows across boundaries. You get steadier execution and cleaner handoffs, which cuts down on the small errors that tend to compound over time.

It seems Gartner emphasizes this Use Case as a marker of maturity: it’s not about more automation, but using the right automation to move the business forward. By linking actions into cohesive workflows with decision points and exception handling, you transform fragmented activities into streamlined business processes.

What this unlocks: If your workflows run end to end, you’ll feel the difference immediately. Approvals and handoffs will happen without manual nudges, and any exceptions will surface early. The work is to oversee processes instead of managing dozens of micro tasks.

Data orchestration: Automating movement and storage

Analytics live or die on the reliability of the pipeline behind the dashboard. At 3 AM, your retail data might need to move from SAP to Snowflake, be validated, then trigger an update to executive dashboards before the morning meeting. That kind of flow can’t rely on spreadsheets, email notifications or ad hoc scripts — it requires systematic orchestration.

SOAPs plug into managed file transfer (MFT) solutions, ETL tools and data lakes to manage the full lifecycle of data movement: ingestion, transformation, validation and delivery. You can build flows that validate data quality, handle exceptions and ensure downstream systems receive accurate, timely information.

I believe Gartner calls out data orchestration because the stakes are high. Poor data hygiene slows decisions, introduces risk and devalues analytics investments. With proper orchestration, your data pipeline becomes a strategic asset rather than a constant challenge.

What this unlocks: Reliable data flows remove the daily uncertainty that slows decision-making. Your analysts don’t have to wonder whether today’s numbers are safe to use. And by the time business users open a dashboard, the underlying pipeline has already done the hard work.

DevOps: Coordinating pipelines across teams

It’s relatively easy to automate a deployment, but it’s much harder to orchestrate everything that comes before and after. When your infrastructure team needs to provision environments, QA needs to run tests and compliance needs to log every step, a simple webhook or CI/CD pipeline isn’t sufficient.

SOAPs can coordinate across your entire development lifecycle, trigger event-based actions and integrate with ITSM and monitoring tools. This coordination is especially valuable when different teams use different tools but need to work together seamlessly.

In my view, Gartner includes this as a distinct Use Case because orchestration here is a force multiplier: it aligns developers, operations and compliance without slowing velocity. By automating handoffs between teams and tools, you reduce waiting time, eliminate manual coordination and maintain an audit trail of all activities.

What this unlocks: Orchestration that supports the DevOps lifecycle ensures your release cadence reflects your engineering velocity. Your dev team doesn’t have to worry whether upstream tasks are complete, and your operations team gets predictable workflows they can trust.

Citizen automation: Putting control in the right hands

Not every routine workflow warrants an IT ticket. An HR manager initiating onboarding or a supply chain planner adjusting inventory levels need their workflows to be accessible without sacrificing governance. As your organization scales, the ability to distribute automation capabilities becomes crucial.

SOAPs support low-code interaction, reusable templates and full audit trails. Users get what they need when they need it, and IT maintains oversight of the entire automation ecosystem. Gartner likely highlights this Use Case because it balances empowerment and control: you reduce shadow IT while still enabling business agility.

What this unlocks: Governed self-service changes how work gets done. You can move faster without losing control because every action runs through the same orchestrated backbone with full visibility.

Your SOAP unifies it all

Every Use Case in the Gartner report points back to a simple truth: orchestration is how you scale automation without multiplying complexity. The best SOAP platforms make that orchestration real across jobs, data, workflows and teams, providing the connective tissue that binds your digital ecosystem together.

As you evaluate your options, look for platforms that support all five Use Cases with equal strength. Your business doesn’t operate in silos, and your orchestration platform shouldn’t either. The right solution will grow with your needs, adapt to new technologies and continuously deliver value as your organization evolves.

RunMyJobs by Redwood offers comprehensive, enterprise-wide orchestration, with deep integration into SAP environments and support for hybrid cloud architectures. Download the full Critical Capabilities report to see an extended analysis of the Gartner Magic Quadrant™ and learn why Redwood was recognized as a SOAP Leader two years in a row.

As soon as teams began trying to extend AI beyond isolated tasks — past the browser tab, outside the development environment or into workflows that cross departments — progress stalled. The models were perfectly capable, but in most cases, the enterprise wasn’t ready to support them.

AI today largely operates in silos:

• Summarizing a document in one tool
• Generating a draft in another
• Answering a question inside a chat window

Those applications are useful, yes. But transformational? No. And certainly not autonomous.

The next phase of AI will operate very differently. Agentic AI promises to reason, plan and participate in the work, not just advise on it. For any AI system to influence real business processes, the organization must first create the environment to support it.

It’s critical to build a foundation for the next decade of AI to operate with clarity, coordination and control.

Why leaders often think they’re ready

When AI experiments stall, the reflex is to look at the model.

• Should the prompt be rewritten?
• Should the model be retrained? 
• Should the team switch providers?

In fact, most AI slowdowns have nothing to do with model quality. They’re caused by the operational surface the model enters. Across enterprises, the same foundational gaps appear again and again, regardless of industry or scale.

1. Work happens in silos. AI has no shared control layer. Automations, scripts, SaaS workflows and departmental tools all run independently. This fragmentation increases the likelihood of “shadow AI” — and the blind spots in security and cost that come with it.
2. Every department uses different guardrails. Access, approvals and policies vary wildly across teams. AI simply can’t follow rules that don’t exist consistently.
3. Workflows assume predictability, but reality doesn’t. Static, rule-based logic breaks the moment conditions change. AI becomes another exception handler instead of a force multiplier.
4. Leaders lack cross-system visibility. Throughput, failures, bottlenecks and downstream impacts are scattered across tools. You can’t operationalize intelligence you can’t see.

These gaps don’t make agentic AI unrealistic, but they reveal what’s missing. To safely give AI the ability to plan and act, enterprises need coordination, governance, adaptability and visibility working together under a unified orchestration approach.

Before autonomy: The architectural fundamentals

Across enterprises making real progress toward AI readiness, one theme is clear: they’ve perfected the architecture underneath the model. These organizations are doing more than just experimenting with clever tools. They’re building the conditions for intelligent systems to operate safely and consistently.

Unification: One orchestration layer to coordinate the work

Imagine an AI system evaluating a delivery delay. It checks order data in one application, inventory in another, customer records in a third and workflow timing in a fourth. Without orchestration, those steps become disconnected guesses. With it, they become a single, synchronized, visible and aligned action path governed by business rules.

A unified layer provides the control plane that keeps all forms of work — human, automated or AI-assisted — moving in the same direction.

Boundaries: Guardrails for scaling intelligence — not risk

Guardrails vary in format, but they all answer the same question: What is safe for this system to do? Instead of a long list, the most effective enterprises keep it simple with:

• Actions that are always permitted
• Actions that require verification or approval
• Actions that are never allowed

When these rules are applied consistently across departments, intelligent behavior becomes predictable. AI stops guessing how decisions should work and starts following the same standards everyone else does.

Transparency: Governance that keeps humans in control

As soon as automation can influence workflows, visibility becomes non-negotiable. Leaders need to see how a decision unfolded, what it touched and why it behaved the way it did. That requires:

• Observability into processes
• Clear documentation of decision paths
• Audit trails that withstand scrutiny
• The ability to unwind or adjust actions when needed

Governance turns autonomy into something accountable, rather than opaque.

Coexistence: A blended environment of deterministic and dynamic automation

Enterprise leaders sometimes assume they must choose between traditional automation and AI-driven adaptability, but the highest performers do the opposite. They preserve their deterministic backbone: the scheduled workflows, validations and rule-based logic that keep operations steady. Then, they layer adaptability where variability actually occurs.

In other words, it’s reinforcement, not replacement. Rule-based processes handle what is predictable, adaptive decision loops handle what isn’t and orchestration brings the two together.

How experimentation becomes an operating model

AI experimentation is happening everywhere at once. Marketing might test a summarization tool, Finance could be exploring anomaly detection and Operations may pilot an automation assistant. The activity is high, but the impact is uneven. Some pilots work, others stall and many echo work already happening elsewhere in the organization.

What’s missing is structure. Modern AI only becomes meaningful when it’s connected, governed and repeatable. That requires shifting from scattered experimentation to an operating model that gives every team the same foundation to build upon.

Read more about building the best foundation for agentic orchestration.

A platform-first evolution in automation

The transformation underway resembles the moment when analytics matured from isolated dashboards into full data platforms. AI is undergoing a similar transition. What begins as a collection of tools eventually becomes an operational discipline shaped by shared infrastructure, shared controls and shared context.

In practice, this means we have to start thinking differently about how AI gets introduced and supported. Investment decisions move away from individual tools and toward foundational capabilities that every team can rely on, like interoperability and visibility. Talent evolves as well, with roles focused on designing supervised automation, not just building models in isolation.

Metrics also expand. Instead of measuring AI success through cost savings alone, executives are beginning to track the health of end-to-end processes: throughput, order delivery rate, consistency, service quality and customer satisfaction, for example. These are the signals that show whether the enterprise is truly becoming more adaptive.

Risk posture changes, too. Rather than waiting for AI to cause a problem, leaders establish guardrails and safety patterns before AI touches a core workflow. True autonomy starts with boundaries.

This evolution marks a larger shift: the move from experimenting with AI to preparing the enterprise for it. When you treat orchestration and governance as shared capabilities instead of departmental add-ons, innovation becomes faster, safer and easier to scale. AI moves from being something scattered teams try out to something the entire organization can trust.

What agentic orchestration will unlock (when the foundation is ready)

Agentic AI at scale remains a future capability, but the directional value is already clear. Once you have orchestration, governance and interoperability in place, you can unlock an entirely new class of capabilities:

• Systems that adapt faster than conditions can destabilize them
• Cross-system decision-making that reflects real business context
• Self-service interactions where users request outcomes, not workflows
• Operations that continue running even when inputs, timing and exceptions change
• Insight that spans applications, dependencies and data in motion

Your teams can gain a level of clarity, context and control that may be elusive today.

The advantage will go to those preparing now

Organizations making progress toward autonomous operations share a common pattern. They’re not racing toward agentic AI, but building the scaffolding that will support it.

That means they’re:

• Consolidating automation under a unified orchestration layer
• Strengthening governance to define how decisions and actions occur
• Insisting on interoperability across systems and tools
• Using AI assistance to improve deterministic workflows
• Piloting new AI patterns in controlled, low-risk environments
• Defining KPIs that reflect throughput, delivery, consistency and service quality

Preparation accelerates innovation, creating an environment where AI can be introduced safely, evaluated clearly and scaled confidently. Enterprises that begin now won’t just be ready for agentic AI. They’ll be structurally positioned to benefit from whatever comes next.

To explore the now, next and beyond of AI, read “The autonomous enterprise” and get a deeper look at how orchestration, governance and preparation shape the path to more intelligent operations.

If your IT automation is running well but you’re finding it harder to scale or innovate, it may be the right moment to consider a jump in WLA technology. And modernization doesn’t have to mean all cloud, all at once; many teams keep key processes on-premises while adopting cloud-based orchestration where it adds value.

Here are nine signs that your organization is ready for a change and how doing so will prepare you for scalability and long-term resilience.

✅ Your team is ready to move beyond daily upkeep

On-premises WLA solutions can fall multiple versions behind because upgrades compete with other IT priorities. Adding hardware to expand capacity feels clunky, and even routine maintenance can put critical workflows at risk. When your IT team is spending more energy on patching and firefighting than planning new initiatives, it’s often a signal you’ve outgrown the old model. Upgrading to a SaaS-based platform is less about replacing what you have and more about celebrating that your automation maturity has reached a point where you’re ready for the next level. 

✅ Manual fixes are crowding out higher-value work

If your operators are babysitting workflows or writing scripts just to keep processes running, you’re not realizing the full ROI of automation. Time is money, and when you spend hours on workarounds instead of optimizing processes, your total cost of ownership (TCO) rises and strategic value shrinks. 

Modern WLA software reduces that manual intervention with event-based triggers, self-service options and automated recovery. Freeing your people from constant fixes means more time spent improving processes and less time chasing failures.

✅ Automation needs to follow workloads into the cloud

Most enterprises are already moving workloads to the cloud, whether it’s data analytics, ERP modules or customer-facing apps. If your WLA doesn’t connect to cloud platforms natively, you’re forced into brittle workarounds that waste time and limit scalability. 

Modernization means orchestrating flawlessly across on-prem, hybrid and multi-cloud environments — AWS, Azure, Google Cloud and SaaS applications — with equal reliability. Modern WLA adapts dynamically to wherever the workload runs.

✅ Visibility gaps are slowing decisions

When leaders don’t have a real-time view of workflows, they’re forced to make decisions based on lagging reports or gut instinct. Outdated WLA tools often lack centralized dashboards or predictive analytics. That leaves IT blind to bottlenecks, failed jobs or SLA risks until it’s too late. 

Modern platforms deliver observability with centralized dashboards, SLA projections and proactive alerts so you can fix issues before they disrupt the business.

✅ Scaling feels harder than it should

Every business faces periods where job volumes soar: end-of-month closings, holiday traffic, product launches. Traditional WLA models can hit limits under pressure, leading to delays and downtime. Some organizations work around this by adding servers and hardware that they only need a few times a year. 

A modern SaaS platforms scales with your business, growing and shrinking with demand, so you only pay for the value you get. That means no scrambling or overbuying.

✅ Maintenance is draining resources

Traditional job scheduling tools can come with hidden costs in the form of specialized staff or consultants and downtime during upgrades. None of that creates business value.

In contrast, a SaaS-based automation platform rolls out updates automatically to minimize downtime and ensure you don’t have to rely on niche expertise. You get true financial headroom, even beyond IT operations.

✅ Security expectations have surpassed your tools

When automation runs financials, healthcare data, customer transactions and other key processes that handle sensitive data, security isn’t optional. Many systems still in use struggle to keep pace with modern cybersecurity expectations.

Today’s automation platforms include role-based access control (RBAC), encryption, continuous patching and audit-ready trails by default. So instead of hoping your system is secure, you can prove it.

✅ AI isn’t part of the equation

If your platform is stuck in reactive mode, you’re missing opportunities to get ahead of issues and continuously improve. Automation isn’t static anymore — it’s intelligent. AI isn’t hype in this space. It’s becoming the standard for enterprises that want reliable, efficient and proactive automation.

The most advanced WLA platforms now layer in AI and machine learning. These capabilities don’t just predict job failures but also recommend optimizations and analyze patterns across thousands of runs. It’s the difference between automation that simply works and automation that amplifies ROI by proactively driving efficiency. 

✅ Users want more control without more risk

When automation tools are too complex, IT becomes the bottleneck. Business users resort to shadow IT, running critical business processes outside governance because the official system is too hard to use. 

Modern WLA turns this on its head with intuitive interfaces, drag-and-drop workflow builders and delegated self-service. When users are empowered, automation becomes a force multiplier instead of a source of friction.

Why readiness matters now — no matter your use case

Every organization is under pressure to do more with less. Outdated workload automation slows you down, increases risk and adds hidden costs. Modernization isn’t about chasing a trend; it’s about putting your business in a position to scale, innovate and compete.

A modern SaaS WLA solution gives you:

• Scalability without infrastructure sprawl
• Deep integrations not only with SAP and other enterprise systems, but also for hybrid and multi-cloud workloads
• Observability for centralized visibility and predictive monitoring
• AI-driven optimization and self-service
• Built-in security and control
• Lower cost of ownership and fewer upgrade headaches

If these signs sound familiar, it may be because your business success has outgrown traditional approaches. That’s a good thing — it means you’re ready to modernize. Acting now lets you turn that momentum into a more scalable, flexible and resilient automation strategy, just as many leading enterprises are already doing.

What happens when you don’t modernize in time? Find out what the aviation industry learned the hard way.

Partner with the leader in WLA

Redwood Software has been helping enterprises modernize automation for decades, across both on-premises and cloud environments. Redwood was also named a Leader two years in a row in the Gartner® Magic Quadrant™ for Service Orchestration and Automation Platforms (SOAPs).

With RunMyJobs by Redwood, we offer the only SaaS-native WLA platform purpose-built for hybrid IT, designed to support SAP and business-critical processes at scale. Because we’ve led in both on-prem and SaaS, we’re uniquely positioned to guide your transition and help you modernize at your own pace.

Talk with a Redwood expert to see how a modern workload automation solution can reduce costs, boost operational efficiency and support your cloud journey.

Together, the two reports give a comprehensive view of the SOAP market landscape, but they remain market-level research, not an assessment of your specific business priorities.

Here, we offer a practical framework for how to translate Gartner’s approach into your own scorecard to evaluate SOAP platforms against your organization’s needs and goals.

Why capability-based evaluation matters

The Magic Quadrant™ is invaluable for seeing which vendors are positioned strongly in the market. It shows who’s executing effectively today and who has the vision and roadmap to meet tomorrow’s demands. But it’s not a detailed interrogation of product features or a guarantee of fit for your particular requirements.

That’s why the Gartner Critical Capabilities companion report is so useful. It zooms in on differentiators — why the SOAP software providers were recognized in particular areas. It asks: How well does this platform execute real-world tasks? How usable is it? What outcomes does it enable?

In the report, Gartner recommends, “When selecting a SOAP vendor, conduct thorough due diligence to understand their specific strengths in innovation, integration and responsiveness to emerging trends, rather than assuming parity in a mature market.”

Inspired by this approach, we’ve built a scorecard you can use to evaluate vendors for your particular purposes, for both functionality and fit,  based on the five SOAP Use Cases.

Key capability domains to score

Each domain aligns with a Use Case from the Gartner report. Below, you’ll find:

• What the domain measures
• Traits to look for
• A 1–5 scoring rubric

1. Operational resilience and IT workload execution 

Inspired by the IT Workload Automation Use Case

Can the platform orchestrate and safeguard large volumes of complex, time-sensitive IT workloads?

What to evaluate:

• SLA monitoring and escalation dashboards
• Automated failover, retry and recovery mechanisms
• Volume throughput and performance under stress
• System auditability and job history tracking

How to score:

2. Hybrid orchestration and workflow flexibility 

Inspired by the IT Workflow Orchestration Use Case

How well does the platform support both business and technical workflows across hybrid environments (on-prem, multi- cloud, SaaS)?

What to evaluate:

• Breadth of pre-built integrations across legacy and modern systems
• Ease of orchestration across teams and technologies (e.g., low-code)
• Flexibility to design, trigger and adapt complex workflows
• Support for both technical and non-technical users

How to score:

3. Data movement and pipeline governance

Inspired by the Data Orchestration Use Case

Can the platform reliably orchestrate large-scale, rule-based data flows across warehouses, lakes and BI systems?

What to evaluate: 

• Availability of connectors for major data platforms (e.g., Snowflake, SAP Datasphere)
• Orchestration of rule-based, event-driven data flows
• SLA tracking for data jobs and throughput performance
• Guardrails like validations, retries and logging

How to score:

4. Empowering business users

Inspired by the Citizen Automation Use Case

Can non-technical users safely create, edit and trigger automations with the right controls?

What to evaluate:

• Guided self-service tools for workflow design and execution
• Guardrails and governance features (e.g., approval workflows, role-based access)
• Training resources and onboarding ease
• Audit logs and rollback capabilities for business-created workflows

How to score:

5. DevOps readiness and automation agility

Inspired by the DevOps Automation Use Case

Does the platform integrate with DevOps toolchains and support agile release cycles? 

What to evaluate:

• Native plugin availability for CI/CD tools
• API maturity and extensibility
• Support for version control, branching, rollback and parallel pipeline execution
• Ability to deploy and manage automation as code

How to score:

Constructing your SOAP scorecard

You don’t need a complex spreadsheet to evaluate SOAPs. Just build a simple table:

Adjust weights based on your priorities. If you’re focused on business agility, you might weigh citizen automation more heavily. If uptime is paramount, prioritize IT workload execution.

This approach doesn’t just tell you which provider offers what you want but the depth to which that capability goes.

Interpreting your results

• 4.5–5.0: Top-tier platform fit, capabilities with depth
• 3.5–4.4: Strong candidate, likely meets core needs with some tradeoffs
• 2.5–3.4: Mid-tier and may require customization or compromise
• <2.5: Unlikely to meet enterprise orchestration needs

Where Redwood leads — and what that signals for you

Redwood Software ranked #1 in all five Use Cases in the 2025 Gartner Critical Capabilities for SOAP report. We believe that reflects more than just functional breadth and confirms Redwood’s ability to deliver real-world orchestration across IT workloads, business workflows, citizen development, data movement and DevOps. This aligns with our mission to unleash human potential through automation fabric solutions.

A SOAP platform is not just a feature set but an enabler of better business outcomes. Use the scorecard above, and download the full Gartner Critical Capabilities report to optimize your search for the right SOAP.

Intelligent orchestration ensures business processes execute reliably, securely and without unnecessary manual intervention. As hybrid environments expand, data pipelines multiply and digital initiatives accelerate, unified orchestration platforms have become mission-critical.

This leap is reflected in the 2025 Gartner® Magic Quadrant™ for SOAP. Vendors are being evaluated on execution in addition to how well they support end-to-end processes, hybrid environments and governance at scale.

If you’re in the process of selecting a SOAP solution, use this practical guide to evaluating your options, with insights inspired by Gartner’s criteria and industry trends.

What is a SOAP — and why does it matter more than ever?

According to Gartner, “SOAPs unify workflow orchestration, workload automation and resource provisioning, extending across data pipelines and cloud-native architectures.”

SOAPs represent the evolution of traditional workload automation beyond job scheduling. These platforms are crucial for bringing order to complex IT environments that span on-premises, multi-cloud and hybrid environments. They matter because they provide a centralized hub to coordinate workflows across diverse systems — both within an organization and across an ecosystem for suppliers and distributors. They reduce risk by providing end-to-end visibility and control and improve business agility by reducing manual intervention.

A modern SOAP coordinates dependencies, enforces service-level agreements (SLAs) and triggers workflows based on events, making it essential for:

• Digital transformation in finance, supply chain and IT operations
• Cloud modernization initiatives
• AI and machine learning (ML) adoption that requires governed data movement
• Compliance with security and regulatory frameworks

The “right” SOAP solution should reduce human error, free up IT to focus strategic priorities and streamline how automation is designed, maintained and governed. It should support faster response to business and market shifts, break down silos by connecting legacy systems and cloud services and enable seamless coordination across your technology ecosystem. Most importantly, it should enhance visibility, control and auditability with a unified view of every process, so your automation is as trustworthy as it is efficient.

Key evaluation criteria when choosing a SOAP solution

Here are six areas to include in your evaluation, inspired by trends surfaced in the Gartner report and common attributes among SOAP Leaders.

Scalability and performance

The platform should be able to handle high volumes of automated tasks without performance degradation. Ask whether it can support millions of jobs per day and how it performs under peak loads. A SOAP must be resilient and elastic enough to accommodate sudden surges in workload without compromising execution times or reliability. Scalability is about sustained performance, not just capacity.

Cloud-native architecture and SaaS delivery

When evaluating a SOAP solution, start with how the platform itself is built and delivered. A truly SaaS-native platform doesn’t just “run in the cloud;” it’s designed for elastic scale, multi-tenant performance and frictionless updates. Look for characteristics like agentless architecture, stateless services, zero-maintenance provisioning and high availability built into the core. These reduce operational overhead and speed up onboarding.

Deployment flexibility and hybrid orchestration support

It’s not just how the platform is built but also how it operates. A SOAP platform must support orchestration across your entire environment, from legacy mainframes to modern SaaS apps, cloud services, containers and DevOps pipelines. Seek flexible endpoint support, native connectors and the ability to run across multiple clouds, regions or tenants without custom scripting or duplicate workflows.

Ease of use and low-code accessibility

Automation should be democratized. Your SOAP platform should provide a low-code interface that enables IT operators, developers and even power users on the business side to design and modify workflows. Features like drag-and-drop workflow designers and reusable templates make it easier to build, test and share workflows. Integrated documentation and governance reduce training time and increase adoption. 

Observability and monitoring

It’s not enough to execute a job. You need to know what happened, why, and what could go wrong next time. Real-time dashboards, job dependency maps, SLA monitors and predictive alerting help teams quickly isolate failures and understand upstream/downstream impact. A strong observability layer turns the SOAP into a diagnostic tool, not just a transaction engine.

AI-powered productivity

It’s key to empower your teams with specific and valuable assistance for using the product and operating the platform to deliver efficient, reliable and observable automation fabrics. AI is now embedded into how automation platforms help users work faster, smarter and with greater confidence. AI features can significantly reduce time-to-value and operational risk. Whether you’re troubleshooting a failed job or optimizing a business-critical process, AI-powered diagnostics accelerate root-cause analysis, helping your teams resolve issues before they cause downstream delays. Equally important is AI’s role in design-time productivity. Context-aware configurations and AI-optimized change management can reduce the friction involved in building new workflows.

Security and governance

Security and compliance should be built in, not bolted on. SOAPs must support enterprise-grade authentication and authorization, including single sign-on (SSO), multi-factor authentication (MFA) and role-based access control (RBAC). They should also be able to encrypt data in transit and at rest and offer detailed audit logs. Look for support for compliance frameworks like SOC 2, ISO 27001 or HIPAA, depending on your industry. Governance features should also enable fine-grained control over who can modify, execute or monitor workflows.

Extensibility and ecosystem

No SOAP platform operates in a vacuum; it must integrate cleanly with your existing infrastructure, applications and cloud services. Look for out-of-the-box connectors, a rich library of APIs and support for event-driven triggers. The more extensible the platform, the more value it will deliver as your tech stack evolves.

Trends shaping the SOAP landscape in 2025

“By 2029, 90% of organizations currently delivering workload automation will be using service orchestration and automation platforms (SOAPs) to orchestrate workloads and data pipelines in hybrid environments across IT and business domains.”

2025 Gartner® Magic Quadrant™ for SOAP report

SOAP solutions are evolving rapidly. Let’s examine a few trends shaping enterprise automation strategies this year.

• Convergence with adjacent tools: Modern SOAPs increasingly overlap with iPaaS, managed file transfer (MFT) and IT Service Management (ITSM) platforms. Expect tighter ecosystems and fewer isolated tools.
• AI-enhanced observability: Predictive analytics, anomaly detection and proactive SLA risk insights are fast becoming differentiators, especially in high-volume scenarios. The report notes that, “By 2029, 75% of SOAP workflows will leverage generative AI (GenAI) to increase troubleshooting efficiency by 50% — up from less than 10% in 2025.”
• Orchestration for analytics workloads: Data must flow faster and more reliably. As AI becomes operationalized, orchestrating data is just as important as model performance.
• Citizen automation: Business users want self-service tools without compromising governance, and IT needs to enforce guardrails. SOAPs now must deliver both to enable scalable citizen automation.
• Centralized control across domains: Fragmented platforms are falling behind. SOAPs that serve as a control plane for hybrid IT, cloud, data and business workflows are rising to the top.

What sets Leaders apart in the Gartner® Magic Quadrant™

According to Gartner Magic Quadrant™ research methodology, “Leaders execute well against their current vision and are well-positioned for tomorrow.” Choosing a Leader as your SOAP vendor doesn’t guarantee success, but it does reduce risk, accelerate ROI and align you with those invested in long-term innovation.

Why organizations are turning to RunMyJobs by Redwood

When enterprises outgrow reactive automation, they turn to RunMyJobs. It’s purpose-built for orchestrating complex, enterprise-wide workloads.

RunMyJobs helps global organizations automate with confidence through:

• SAP Endorsed App, Premium certification — SAP’s highest standard for performance, security and integration
• Robust hybrid connectivity to seamlessly connect on-premises systems (e.g., ERP, WMS, MES) with multiple public cloud services
• Event-based triggers and integrated data management
• SaaS-native, agentless architecture built for scale, with no infrastructure maintenance
• Built-in observability via Redwood Insights with pre-built dashboards and the ability to customize
• AI-powered productivity enhancements that range from knowledge access to troubleshooting to actual design and development of automation workflows
• Low-code workflow design for both IT and business users
• Enterprise-grade security and compliance
• Decades of automation expertise and two consecutive years of being named a Leader in the Gartner Magic Quadrant™ for SOAP

Choosing the right SOAP solution means choosing the foundation for your automation future. Make the investment count — for what your business needs today and what it will demand tomorrow. Read the full analyst report today.

Forecasting and replenishment (F&R) works the same way. To the customer, it’s simple: the product they want is available where and when they want it. But what got it there was a full production involving forecasting systems, ERP, POS, purchase orders, distribution centers — each with their own scripts. 

Take the case of Target Canada. They had ambitious plans, shiny stores and plenty of product in stock. But backstage, systems weren’t talking to each other. Some shelves stayed empty while others were overstocked, and many customers walked out or didn’t show up at all. The two-year production bombed big-time, resulting in a multi-billion-dollar loss. “Ticket sales” didn’t even cover the cost of performances in this scenario.

Opening night: The performance customers see

F&R is the entire performance from the moment you draw the curtain back. It’s what the audience (your customers) experiences when they shop. Your forecasting engine is the lead actor, but it can’t carry the whole show alone. It depends on a cast:

• ERP systems handling orders and procurement
• POS systems sending daily sales signals
• Warehousing and logistics making sure the right props (products) land on stage
• Replenishment planning and allocation tools managing cues

If these players don’t work together well, the audience will see the mistakes: empty shelves, markdown bins and lost orders, to name a few.

Missed cues: Why supply chains go off script

Even seasoned companies misstep when the backstage crew isn’t in sync. In supply chain terms, that means F&R falls apart when the systems behind them aren’t connected or coordinated.

Take siloed systems, for example. ERP, POS and warehouse management each follow their own script, and none of them talk to each other. That disconnect means planners may not see when a promotion is running, when seasonality is driving spikes in demand or when external events disrupt supply. Without those inputs flowing cleanly into the forecast, replenishment planning quickly goes off track. It’s like three actors reciting different versions of the same play — it’s confusing, messy and painful to watch.

Manual workarounds are another sign of a shaky production. When planners resort to spreadsheets to patch gaps or re-sequence orders, it’s like stagehands rushing onto the set with duct tape mid-performance. The show goes on, but the cracks are obvious.

Rigid, batch-driven processes add another layer of risk. Imagine trying to run a live play using only rehearsed recordings. The story would fall flat the moment something unexpected happened. And the same goes for replenishment runs that can’t adapt when demand shifts suddenly, such as when there’s an unforeseen weather event.

Then there’s the lack of visibility. Without clear lines of sight into whether a job has started, finished or failed, supply chain leaders are left waiting to see if the actor will make their entrance. By the time they realize the cue was missed, the audience already knows.

The outcome of all these broken scenes? Outdated forecasts, replenishment delays, high carrying costs and frustrated customers who don’t come back after intermission.

The director’s chair: Keeping every scene in sync

An orchestration solution like RunMyJobs by Redwood acts as the director behind the curtain, ensuring every system, transaction and dependency plays its part. Think about the challenge of planning a holiday promotion: Forecasting modules may generate a strong demand forecast, but if order proposals don’t trigger on time or distribution centers can’t see accurate inventory levels, the campaign won’t be successful.

With RunMyJobs, order forecasts, replenishment planning, purchase orders and automatic replenishment proposals are kept in sync with demand planning and forecasting algorithms. That means safety stock calculations adjust automatically when seasonality spikes, promotions launch or future demand signals arrive from POS sales data. It also means master data issues are flagged and corrected before they cascade downstream.

This is true whether you’re running SAP F&R, IBP, Retail and Distribution Industry Solutions, MM, APO or connecting to non-SAP systems — RunMyJobs keeps the performance on track no matter the complexity of your tech stack. You’ll be able to respond faster to factors influencing demand, like promotions, pricing changes or unexpected stockouts, while reducing manual interventions. 

Orchestration transforms F&R from a fragile balancing act into a resilient, repeatable process that adapts to real-world conditions.

Standing ovation: Course-correcting with orchestration 

The value of orchestration in F&R shows up in the KPIs that matter most: gross margins, order fill rates and customer satisfaction.

Treat F&R like the production it is

In retail and distribution, forecasting and replenishment is mission-critical. It’s not a solo performance but an ensemble production that needs perfect timing, cues and orchestration. 

RunMyJobs provides the automation fabric that keeps your show running. Global retailers and distributors trust it to bring order to complexity and deliver consistent, applause-worthy results. 

Book a demo to see how RunMyJobs can optimize your F&R process end to end.

The problem is, “just working” isn’t the same as being ready for what’s coming next, especially if you care about SAP’s evolution and the massive role AI is playing. In a world where digital transformation now means becoming an intelligent enterprise built on real-time data, you can’t afford not to make use of the “best of the best” solutions.

Luckily, SAP gives us an easy way to determine which compatible solutions the company most strongly stands behind: SAP Endorsed App Premium certification.

SAP Endorsed App: More than just a badge

SAP Endorsed Apps aren’t ordinary partner solutions. This invitation-only program highlights solutions that help you with strategic business challenges not directly addressed by core SAP functionality. 

SAP Endorsed App status is the highest level of certification SAP offers, and it isn’t handed out lightly. It signals to customers that the solution has been extensively tested and validated to meet SAP’s highest standards for performance, security and integration.

Being an Endorsed App means a solution has been rigorously evaluated and passed SAP’s most demanding Premium certification standards. Every angle is tested to ensure the solution truly stands up to real-world enterprise demands, even in the most complex hybrid environments. Only solutions that are widely used by SAP customers, future-aligned and proven to deliver outstanding customer value earn this highest level of SAP trust.

SAP Endorsed App for workload automation

Taking advantage of SAP’s next-generation capabilities is particularly important when it comes to workload automation, the backbone of your mission-critical processes. SAP CEO Christian Klein envisions a world in which ERP, automation, data and AI all work together in one cohesive ecosystem. Your processes should run end to end, intelligently orchestrated rather than stitched together. If your automation layer isn’t deeply integrated and future-ready, it becomes an anchor dragging you down. And if your workload automation partner isn’t deeply aligned with SAP, you’re going to hit bottlenecks sooner than you think.

That’s why RunMyJobs by Redwood becoming a Premium certified SAP Endorsed App matters so much. You know your automation will be not just compatible but optimal, now and into the future.

Certified vs. optimal integration

Many job scheduling solutions are certified to connect to SAP systems, even RISE with SAP. And that’s good, but it’s only the first step. Basic certification means a scheduler has been tested to connect and perform standard tasks, but it doesn’t tell you how it integrates, what extra infrastructure you need or whether it supports a clean core without workarounds and fragile custom code.

It’s kind of like giving your teenager a learner’s permit. Sure, they’re legally allowed to drive, but would you hand them the keys and say, “Go ahead, take your friends to the basketball game tonight … and use the freeway”? Probably not. You know that true readiness involves more than basic certification. It’s about trust, experience and minimizing risk — for the driver and everyone else on the road.

RunMyJobs is the experienced, fully licensed driver: the only workload automation solution that is an SAP Endorsed App, Premium certified. Thus, it’s optimized to run in complex SAP landscapes, including RISE with SAP, Business Technology Platform (BTP) and Business Data Cloud (BDC). 

It’s not about whether your automation connects to SAP. It’s whether it truly unlocks SAP’s full value, without compromise.

True future-proofing: Not just a fancy marketing slogan

We all see “future-proof” plastered across marketing materials. But real future-proofing isn’t a tagline. It means what’s being offered is designed to evolve, not just function today.

With SAP Endorsed App status, RunMyJobs is verified to keep pace with SAP’s roadmap. There is a regular cadence for SAP and Redwood Software to collaborate and align product roadmaps. What you get from this: reduced risk, faster time-to-value and confidence that your automation engine won’t become the bottleneck when it’s time to embed AI into your core business processes. So when we talk about RunMyJobs being “future-proof,” we’re not throwing around empty words. 

Don’t run your business on a learner’s permit. You need a solution that’s been trained, tested and trusted to navigate the entire journey confidently, even if the road ahead is uncertain.

Watch the video below to learn more about what RunMyJobs’ SAP Endorsed App status means for your business.

See more about RunMyJobs in the SAP Store.

But what happens after the fire is out? This is where you make real, lasting improvements. This is the world of problem management: the forensic investigation into the root cause of an incident to ensure it never happens again.

Redwood Insights is the essential tool for this investigation in RunMyJobs, enabling you to identify trends that are critical for long-term problem resolution. With persona-based dashboards that visualize near-time historical execution data, Redwood Insights allows you to move beyond guesswork and find the root cause of your most complex operational problems.

This post explores how you can use Redwood Insights to transition from a reactive operational posture to a proactive one, using data to solve complex issues and optimize your automation landscape.

Core challenges of effective problem management

Without the right analytical tools, it’s difficult for you to move from a “hunch” to a data-driven conclusion about the root cause of an issue. Teams often lack the aggregated historical data needed for a proper investigation. This leads to two common, frustrating scenarios:

• The major incident post-mortem: A critical production process failed last night, causing significant disruption. The incident team resolved it, but the question remains: Was it a one-time anomaly, or is it a symptom of a deeper flaw that will cause another major outage soon?
• The “death by a thousand cuts:” A seemingly minor job fails intermittently, causing small disruptions. You log it as a low-priority incident every time and manually fix it. No single incident is big enough to warrant a major investigation, but the cumulative impact on team resources and user confidence is significant.

Real-world problem management scenarios with Redwood Insights

Let’s look at how Redwood Insights helps teams move from putting out fires to preventing them through data-driven investigations into both major incidents and recurring annoyances.

1. The major incident post-mortem – anomaly or systemic flaw?

The process: Following a major outage of a critical data warehousing job that was resolved by the on-call team, you’re tasked with conducting a root-cause analysis to prevent recurrence.

The investigation with Redwood Insights:

1. You open the Job Insights report for the failed job to get a complete historical view.
2. You use heat maps to see if failures have ever correlated with this specific date or time of month before, trying to identify patterns.
3. To determine if this was an infrastructure issue, you switch to the Job Server Analysis dashboard. This allows you to quickly rule out a systemic problem by comparing performance across your environment. 
4. Confident that the infrastructure is sound, you return to the job’s execution data. As you analyze the widgets, you clarify the situation using a smart narrative, powered by AI: a simple, natural-language summary of the data.

The business outcome and ROI:

• Action taken: Based on this clear, data-driven context, you can confidently classify the issue. You document the anomaly and close the problem record, avoiding an unnecessary and costly investigation into a one-off event.
• Business outcome: This data-driven approach avoids wasting resources chasing ghost issues while ensuring that genuine systemic risks get the attention they deserve.
• ROI: This leads to improved long-term service stability, more efficient use of skilled engineering resources (who now solve real problems) and increased business confidence in the automation platform.

2. Solving the recurring problem with data

The process: An end-of-day reporting workflow has been failing intermittently for weeks, creating a backlog of low-priority incidents.

The investigation with Redwood Insights:

1. You begin your investigation on the Operator Overview dashboard. Your eyes are immediately drawn to a widget highlighting the “top ten jobs with most frequent failures,” which confirms this reporting job is a chronic offender that needs attention.
2. You analyze the job’s history and use heat maps to discover a clear pattern: The failures almost always occur on weekday afternoons. 
3. To understand why, you pivot to the Queue Analysis dashboard to drill down into the systems involved. Here, the data clearly shows that when the reporting job fails, queue wait times are consistently high, indicating resource contention is the likely culprit.

The business outcome and ROI:

• Action taken: With definitive proof of the root cause, you submit a change request to create a dedicated queue for the reporting workflow, a targeted improvement based on historical data.
• Business outcome: The recurring incidents stop completely. The business service becomes reliable, and the stream of low-priority tickets ceases.
• ROI: This eliminates the hidden operational cost of repeatedly fixing the same small issue, frees up your Operations team from repetitive tasks and improves the reliability and timeliness of service delivery.

Your toolkit for proactive problem management

These tools give you the operational visibility and historical context to take IT operations from reactive troubleshooting to a data-driven, intelligent function.

• Identify recurring issues: Use the Operator dashboards to prioritize the most impactful, systemic problems by highlighting key metrics, such as the top ten failing jobs.
• Correlate failures to find patterns: Use interactive widgets like heat maps to uncover underlying triggers for recurring problems by correlating failures to specific dates or other factors.
• Isolate system-specific problems: Use the Job Server Analysis and Queue Analysis dashboards to understand if failures are application-specific or tied to a particular component, which is crucial for problem management.
• Drive data-driven improvements: Use the detailed Job Insights and Workflow Insights dashboards to perform targeted analysis, enhancing processes through redesign or resource reallocation based on historical performance data.

From reactive firefighting to strategic reliability

Redwood Insights provides the essential tools for a mature problem management practice. It allows you to move beyond the immediate incident and analyze historical trends to find and permanently eliminate the underlying causes.

The result is a more stable, reliable and optimized automation environment. This leads to fewer outages, more efficient use of IT resources and consistently more timely and reliable service management.

Watch this video preview of Redwood Insights to learn more.

Ready to move beyond firefighting and start solving problems for good? Discover how Redwood Insights can power your problem management process. Book a demo of RunMyJobs today.

It’s a disconnect that’s quickly becoming unsustainable. While the pace of AI adoption is moving faster than other disruptive innovations, it simply won’t work if the rest of IT doesn’t catch up. And as SAP made clear at SAP Sapphire 2025, there’s no value in building AI on a shaky foundation.

The new mandate: Modernization beyond ERP

SAP’s strategy has evolved beyond ERP. SAP CEO Christian Klein says true transformation is now about incorporating the “flywheel” of applications, data and intelligence. The implication is that SAP Business Technology Platform (BTP), embedded AI and unified data models aren’t peripheral to the core — they are the core.

The explosion of SaaS tools hasn’t produced better outcomes. In his SAP Sapphire Orlando 2025 keynote, Klein noted that global productivity growth has slowed rather than accelerated because too many businesses are duct-taping together apps and automations without the foundation to make them work together.

The implication is clear: You can’t just modernize your ERP and call it a day. Supporting systems, especially those running behind the scenes, such as workload automation (WLA), must evolve in lockstep. Otherwise, you’re introducing friction into every cross-system process (and therefore, AI model) you run.

Old schedulers, new risks

Traditional job scheduling tools were built for a different era. They rely on locally installed software, custom scripts and fragile connections to coordinate batch jobs in static environments. They were never designed for real-time, intelligent processes across cloud-native applications and rapidly evolving AI models.

Sticking with these tools introduces unacceptable risks:

• Operational complexity from maintaining brittle, outdated architecture
• Technical debt from endless scripting and patchwork connectors
• Challenges with maintaining clean core principles
• Fragmented automation across SAP and non-SAP systems
• Inability to leverage SAP’s AI roadmap due to data silos and latency  
• Delayed time-to-value from SAP innovations

You can’t derive reliability and maximum value from AI if your job scheduler is stuck in the past.

Why AI fails without clean, timely data

It’s easy to think AI fails because the models are wrong. But in enterprise environments, the more common culprit is something far less glamorous: bad data. When job scheduling is not modernized, it can quickly become unreliable or disconnected and fail to feed AI systems with what they need to produce in-depth, accurate insights. When they deliver irrelevant or dated insights or hallucinations, it undermines trust in the intelligence you’re trying to deploy.

AI can’t magic its way past old and brittle plumbing that was already on the brink of needing replacement. Trying to update your kitchen or bathroom with fancy new showerheads and faucets with all kinds of bells and whistles may make it look nice, but the water that’s critical to its functioning may struggle to get there at the right time and temperature. A remodel will always require a certified inspection of the pipes and supporting foundation to ensure they work safely and reliably with the upgraded fixtures.

No workaround necessary: The modern approach to WLA

SAP has been loud and clear about the clean core mandate. What was once a push to keep ERP extensibility under control is now a requirement for AI readiness. SAP’s vision of a “fit-to-suite” architecture, where apps, data and automation are in harmony, can’t happen if your WLA layer brings discord into the mix.

Trying to keep your legacy scheduler working is like bringing a VHS tape to a Netflix pitch meeting. Sure, you might find a dusty adapter somewhere in the back closet, but you’ll be miles behind before you even press play. No amount of workarounds will make outdated technology compatible with a world that’s already streaming ahead.

Modernizing WLA for SAP and non-SAP processes means orchestrating every part of your business to be faster and more intelligent. It means having:

• Cloud-native SaaS that orchestrates processes across hybrid environments without additional infrastructure
• Frictionless architecture that provides a singular secure gateway to connect with every SAP and non-SAP application, reduces maintenance and eliminates failure points 
• Deep SAP integration that aligns with SAP product roadmaps and innovation strategies
• Pre-built templates and connectors to accelerate time-to-value without violating clean core
• Centralized orchestration for SAP and non-SAP processes from a single interface

Automation purpose-built for an SAP cloud and AI future

Redwood Software and SAP share a trusted partnership built on over 20 years of co-development, innovation and roadmap alignment, making RunMyJobs by Redwood a strategic extension that maximizes the ROI of your SAP investments.

What sets it apart?

• SAP Endorsed App, Premium certified: RunMyJobs reduces risk, accelerates time-to-value and offers long-term reliability to SAP customers. It’s certified across a broad range of SAP technologies, meeting SAP’s highest standards for performance, security and integration. It delivers native functionality and deep integration across complex hybrid and cloud deployments, with built-in, SAP-specific templates and connectors that eliminate custom code and scripting. This supports clean core strategies and helps customers solve critical business challenges more efficiently.
• The only WLA solution included in the RISE with SAP reference architecture: RunMyJobs is included in the RISE reference architecture through managed services offered and delivered by SAP Enterprise Cloud Services (ECS). ECS handles the direct installation and maintenance of the RunMyJobs’ secure gateway connection within your RISE landscape, eliminating the need for extra infrastructure, custom workarounds and friction in the RISE journey. You can also opt into additional ECS-managed services for enhanced monitoring of SAP processes automated with RunMyJobs, improving visibility and enabling proactive issue resolution.
• Co-innovation with SAP BTP and Business Data Cloud (BDC): Get the latest connectors for SAP Analytics Cloud, SAP Datasphere, SAP Integration Suite, Databricks and more.

Proof that AI-ready automation works

What defines AI-ready in the context of WLA? It’s more than speed and scale. 

Your processes are orchestrated, not just scheduled. You’re connecting tasks and dependencies across SAP and non-SAP environments using event-driven automation.

Governance is built in. You have visibility and control over every job and data flow, from development to execution to exception handling.

Business value is clear. Automation is no longer a backend utility but a strategic driver of innovation, efficiency and competitive advantage.

These elements have already been realized by companies that have modernized with RunMyJobs.

• RS Group, a global industrial distributor, modernized its legacy job scheduler as part of its digital transformation and supply chain operations improvement programs. The company now runs business operations across 26 global markets daily, maintaining job reliability above 99%, and have eliminated Priority 1 and Priority 2 incidents in critical operations for over a year.
• UBS, one of the world’s largest financial institutions, relied on RunMyJobs to replace a legacy scheduling solution that couldn’t scale with the complexity of its SAP environment. UBS transitioned to RunMyJobs for its cloud-native architecture and reliability. The company built a cleaner automation landscape, achieving faster recovery from exceptions and future-proofing its foundation to support advanced analytics and AI-powered compliance.
• Centric Brands, a leading lifestyle brand collective with a complex ecosystem of SAP and non-SAP systems, used RunMyJobs to consolidate multiple legacy scheduling tools and modernize its WLA. By eliminating manual job chains and replacing legacy scripts with standardized, centralized automation, Centric increased visibility across end-to-end processes and significantly reduced errors. Unifying orchestration improved operational efficiency and positioned Centric to adopt AI-driven forecasting and planning tools without needing to overhaul its backend infrastructure.

Rather than being a bolt-on scheduler, RunMyJobs builds automation fabrics that prepare your SAP environment for embedded AI and intelligent processes.

AI-ready businesses don’t wait

SAP’s future is already unfolding, and AI is at the center. But its effectiveness depends on the quality and timing of your automation. If your job scheduling can’t keep up, neither will your strategy. The decisions you make now will determine whether your organization will be ready to act on AI opportunities or stay stuck reacting due to technical limitations.

Modernizing your ERP isn’t enough. You need an orchestration layer that aligns with SAP’s direction, accelerates transformation and eliminates risk. RunMyJobs gives you that edge.

When your automation is fit-to-suite, your business is fit for the AI future. Explore how RunMyJobs future-proofs your SAP ecosystem.

AI was simply everywhere at this year’s events. From Christian Klein’s keynote to the show floor demos, it was the foundation of nearly every conversation. But beneath the buzzwords and bold visions, I noticed one question kept surfacing: How do you actually do it? How do you make AI actionable inside the day-to-day workings of an enterprise?

That’s the question we were thinking about at the Redwood Software booth and in our customer sessions and roundtables. It was fantastic to see the energy this year: standing-room-only demos, deep discussions with IT and business leaders and a steady stream of customers stopping by to share what they’re already doing with job scheduling, orchestration and workload automation (WLA). The excitement was real, but the deeper story was about who’s already rolling up their sleeves instead of just dreaming about digital transformation that actually realizes the value of AI.

Redwood was proud to be recognized for the second year in a row with the SAP Pinnacle Award in a category honoring innovative partners that provide economically relevant solutions, validating our ability to consistently drive high adoption and ROI for SAP customers. We also announced that RunMyJobs by Redwood is now an SAP Endorsed App, Premium certified — the highest level of SAP verification, indicating outstanding customer value. 

The best part? We’re not talking in hypotheticals. These milestones are a testament to the real-world outcomes our customers achieve when integrating with the latest SAP technologies, maximizing the value of their SAP investment. We saw that in full color in sessions and roundtable discussions with RS Group and others, whose teams shared striking results they’ve achieved using RunMyJobs. They haven’t been waiting for the AI wave. Instead, they’ve been preparing for it by modernizing their WLA. And it’s paying off.

We’re making business AI real as we drive digital transformations that help customers thrive in an increasingly unpredictable world. 

Christian Klein, CEO of SAP

Klein’s sentiment rang true throughout the event, especially his keynote theme: To thrive in an AI-powered world, it’s not enough to modernize ERP. Foundational processes, especially the ones running behind the scenes, must be intelligent, agile and orchestrated. WLA platforms like RunMyJobs are already doing the work of preparing SAP landscapes for AI by coordinating processes end to end, orchestrating the tasks that drive efficient data pipelines and ensuring the reliability that AI output depends on.

Redwood customers leading the charge

SAP made it clear: the future isn’t about cobbling together best-of-breed tools. It’s about building a smart, cohesive suite. That suite extends beyond core ERP to include the applications and automation fabrics that make an entire business run. Redwood customers are already there.

RunMyJobs isn’t a standalone job scheduler. It’s the connective tissue for automation fabrics across SAP and non-SAP systems, delivering the kind of real-time orchestration that complex, data-intensive environments demand. Redwood’s shared product vision with SAP is helping customers optimize operations to scale with AI. That alignment is also what earned RunMyJobs its SAP Endorsed App status.

We spotlighted compelling Redwood customer stories at SAP Sapphire this year, including the following.

RS Group: Transforming global supply chain operations for a demanding market

As a global industrial distributor, RS Group faces an unforgiving supply chain environment. Before RunMyJobs, they couldn’t even run business operations processing (BOP) daily for all 26 markets they serve. The complexity was enormous. They had to stagger market runs, which put customer promises, such as delivery timelines, at risk.

Using RunMyJobs to re-engineer processes and workstreams and optimize job logic, they now run BOP for all 26 markets daily. 

We now meet our promise to our business and customers. 

Dharmesh Patel, Head of SAP Development & Services, RS Group

But that was only the beginning. Previously, RS Group faced issues with poor monitoring, alerting and visibility, leading to frequent Priority 1 (P1) and Priority 2 (P2) incidents in critical operations like order processing and warehouse management. With RunMyJobs, they introduced custom alerting, rebuilt job frameworks and created a governance model for continuous improvement.

This isn’t just operational success. It’s setting the stage for AI readiness, because AI needs more than just access to data. It needs reliable, actionable data at the right time, integrated into the processes that power the business. RS Group is ready. When you run a global supply chain, “ready” isn’t a luxury.

Ready on day 1: How fit-to-suite automation prepares you for the AI future

The real takeaway from SAP Sapphire wasn’t that AI is coming. It’s that AI is already here, and the companies reaping the benefits are the ones that did the foundational work early. Redwood customers like RS Group have already modernized their WLA. They’re not bolting on AI. They’re ready for what’s happening now and what’s to come because their automation is fit-to-suite: deeply integrated, spanning SAP and non-SAP systems and built for scale and AI innovation.

RunMyJobs provides the automation fabrics enterprises need to orchestrate complex, cross-system workflows and support the data pipelines AI depends on. It connects SAP S/4HANA to the hybrid architectures, business process layers and related data AI needs to drive better, faster decisions and more efficient attainment of business outcomes.

When your business runs on well-managed, intelligent processes, you don’t just hope your AI strategy will work — you know it can.

An obvious and undeniable message of SAP Sapphire 2025? WLA modernization isn’t a side project. It’s a prerequisite. See how Redwood supports SAP customers in future-proofing their ecosystems.

Analytics power nearly every strategic business decision, but only when they’re delivered in context, on time and aligned with the end-to-end processes and stakeholders they’re meant to inform. That’s why forward-looking insights are no longer optional.

Whether you need to spot cash flow risks before they affect liquidity, adjust production plans before disruptions ripple downstream or re-forecast inventory before you notice a sales dip, your ability to predict and respond depends on analytics that move with your operations.

SAP Analytics Cloud (SAC) was built for exactly this kind of intelligent analysis, forecasting and agile planning. It brings together business intelligence, planning and predictive analytics in one place so you can always know where you stand and model future scenarios to be ready for what’s coming instead of what has just occurred.

But insights alone don’t create outcomes. Unless they’re integrated into an operational process, even the most advanced insights can’t drive impact. Worst case, they could guide you to wrong decisions and negative consequences.

The hidden liability of siloed analytics

Even in a powerful, cloud-based platform, analytics can still fall out of step with the business. Your systems might be automatically refreshing and publishing dashboards or verifying outputs, but if they’re doing so while disconnected from your end-to-end processes, you won’t be able to apply these outputs meaningfully to your role.

You shouldn’t have to wonder whether your numbers reflect just a small snapshot of what’s happening or the full sequence of updates across systems. That uncertainty chips away at trust, and it’s more than frustrating. It’s costly.

Take a high-stakes industry like manufacturing, in which a day-old production forecast can misalign plant operations with actual demand. Or healthcare, where even brief gaps in staffing or patient volume data can impact care and compliance. Siloed analytics workflows aren’t useful or timely in supporting complex, mission-critical processes that need to run continuously.

SAP Analytics Cloud: Built for insights, ready for orchestration

SAC is already a strategic hub for business insights. It connects natively to SAP S/4HANA, SAP Datasphere, SAP BusinessObjects and Databricks. It helps unify planning and analysis across departments and roles. But what transforms SAC from a great tool into an essential one is where it fits in the big picture of your business.

Think about it this way: SAC tells you what’s happening or what’s about to happen. It can publish dashboards and refresh models on a schedule, but to act on those insights in time, you need analytics to match the continuous rhythm of your operations instead of sitting still. 

Orchestration with an advanced workload automation platform can embed those steps inside complex, multi-step job chains that include dozens of tasks, from ETL and ERP updates to file transfers, reconciliations, condition checks or even alert triggers. Reports can be triggered by events, conditions or thresholds from within SAP or external systems, then distributed, published or escalated based on logic.

Instead of standalone data, you get analytics in motion. What does this look like in the real world?

• A multi-step financial close process automatically refreshes and publishes the appropriate dashboards at each stage as part of the normal process chain of the closing cycle — without needing to be managed in a separate analytics workstream
• A disruption in supply chain data from SAP S/4HANA or SAP Datasphere triggers a refresh of demand forecast models in SAC as part of your continuous supply chain processes
• Executive dashboards are scheduled within a larger workstream to update nightly and adjust to special schedules around holidays, peak seasons or system maintenance windows

These reports don’t stay isolated. They’re embedded in your broader business workflows and reacting to real-world conditions. In other words, they align with your operational priorities.

What full automation delivers

With SAC jobs built into your end-to-end business processes, you see the value compound across your organization.

There won’t be a need for separate analytics workstreams anymore. Dashboards and models, connected to your end-to-end processes, will update based on the logic you define at the cadence your business needs.

Analytics will follow the pace of your business, not the other way around. That means your leadership team can get ahead of issues and make proactive decisions. Everyone will see the same numbers, which are built on the same trusted foundation.

Instead of ad-hoc report refreshes or support tickets, your analytics will run as part of a monitored, auditable job chain, giving your key stakeholders insights as they happen in the everyday flow of business.

Ultimately, you’ll be automating business readiness — not just accurate or timely reporting.

Making insights flow: SAP Analytics Cloud + RunMyJobs by Redwood

The new RunMyJobs connector for SAP Analytics Cloud makes it easy to orchestrate your analytics processes within broader, mission-critical job chains without adding complexity or rework.

With the connector, you can:

• Include SAC alongside ETL jobs, S/4HANA transactions, file transfers or external alerts
• Monitor your analytics within each complete job chain from a single pane of glass
• Refresh and publish reports automatically as tasks in end-to-end process rather than siloed triggers
• Tie analytics tasks to business events, conditions or schedules from SAP and non-SAP systems

There’s no need to replace SAC’s native scheduling functionality. With RunMyJobs, you elevate its capabilities by embedding them into more complex and interdependent processes. SAC gives you top-notch insight, and RunMyJobs makes sure it’s delivered at the tempo you need and as part of the complete picture.

Know what’s happening and be ready to act on it. Explore more about how to orchestrate your SAP data pipelines with RunMyJobs.

This is why observability is key. A concept originating from IT monitoring and AIOps, observability goes beyond simply monitoring what you think is important. It’s about being able to ask any question about your systems and understand their internal states based on the data they produce: logs, metrics and traces.

Applying observability principles to workload automation and Service Orchestration and Automation Platforms (SOAPs) can help you handle complexity and orchestrate peak performance in your mission-critical automation fabrics.

Automation is leveling up

Several key trends are driving the need for sophisticated automation. Industry 4.0 adoption, the relentless pursuit of supply chain resilience and the demand for real-time business intelligence all require a new level of powerful and transparent automation. 

This requires a new kind of automation. SOAP solutions play a critical role, enabling real-time coordination of smart devices and systems. They provide centralized control, from production schedules and quality checks to predictive maintenance. Automation platforms are empowering organizations to guarantee the reliability of intricate IT and business services at scale.

What observability really means

Observability is built on three core principles:

1. Telemetry: Gathering rich data from your systems. This means collecting logs, metrics and traces to capture every facet of their behavior.
2. Context: Adding meaningful information to this data. Understanding the relationships and dependencies between different components is crucial.
3. Exploration: Empowering you to ask any question and investigate system behavior, even questions you didn’t anticipate.

Unlike traditional monitoring, which focuses on predefined metrics and alerts, observability allows you to proactively investigate issues, identify root causes faster, improve system performance and enhance agility. It’s about moving from reactive firefighting to proactive optimization.

As the automation industry changes to adapt to new business models and an increase in technical and data complexity that shows no signs of slowing down, focusing on observability as a key concept in the automation space is critical.

Applying observability to workload automation and SOAP

Observability brings significant value to workload automation and SOAPs, turning abstract job chains into fully transparent systems. It gives operators and administrators the tools they need to answer key questions like: Which jobs are running late? Where is the bottleneck? What impact will a failed step have downstream?

Here’s how that looks in practice:

• Integration monitoring: Tracking the health and performance of integrations with other systems and applications, such as ERPs, CRMs and cloud services
• Job-level insights: Monitoring individual jobs or tasks within workflows, analyzing resource utilization, tracking error messages and measuring performance metrics
• Predictive analysis: Leveraging observability data to predict potential issues and optimize automation performance before disruptions occur
• Workflow visibility: Gaining deep insights into the execution of your automated workflows and understanding dependencies, tracking execution times and pinpointing success/failure rates

To effectively leverage observability, your workload automation or SOAP solution needs specific capabilities:

• Alerting and automation: Enable proactive alerting based on observability data and trigger automated actions to address issues.
• Contextualization: Enrich data with context using tags, metadata and workflow IDs for meaningful analysis.
• Data collection: Robustly collect detailed telemetry data (logs, metrics, traces) from all components of the automation platform and its integrations.
• Visualization and analysis: Provide powerful tools for visualizing observability data, creating dashboards and performing root cause analysis.

Consider these real-world examples.

Supply chain optimization 

By applying observability principles, organizations can gain end-to-end visibility into their complex supply chain workflows, tracking the execution of various automated procurement, manufacturing and logistics tasks. This deep insight allows them to pinpoint exactly where bottlenecks are occurring, such as delays in raw material processing or inefficiencies in distribution, ultimately unlocking hidden efficiency and ensuring greater supply chain resilience against disruptions.

Business process assurance

Observability provides the granular detail necessary for troubleshooting failures in critical business processes like order processing or financial transactions, going beyond simple error notifications to reveal the precise step and underlying cause of the issue within the automated workflow. By monitoring individual jobs and integrations involved in these processes, organizations can quickly identify whether a problem stems from a failing application connection, a data validation error or a resource constraint. Thus, it enables faster resolution and minimizes costly disruptions to essential business operations.

Resource efficiency

Through observability, organizations can monitor the resource utilization of individual automated tasks and workflows, gaining a clear understanding of CPU usage, memory consumption and I/O operations. This detail allows them to identify underutilized resources that can be reallocated or optimize the scheduling of resource-intensive jobs to avoid contention. The outcomes of wisely navigating complexity instead of letting it overtake operations? Improved overall efficiency and reduced operational costs.

Properly implemented, observability allows you to predict disruptions instead of reacting to them.

Knowing what’s about to happen: AI in observability and automation

With observability in place, automation becomes more than a set-it-and-forget-it system. AI is allowing businesses to use automation to highlight weak points, adapt to changes and continuously improve. Its integration with observability and automation platforms unlocks new levels of efficiency and intelligence.  

AI enhances observability with smart narratives for data views that enable deeper data exploration and deliver real-time operational insights. This empowers teams to orchestrate workflows in perfect harmony and predict bottlenecks before they happen.

AI-driven automation is also moving beyond simple task execution to more complex, autonomous operations. The near future will include AI that operates autonomously to optimize performance and resolve issues, collaborates with users to automate complex tasks and provides instant information and guidance.

By integrating AI, automation platforms are evolving to provide a seamless experience, taking users from data to insights to action in a single step.

Redwood Insights: Observability built for orchestration

The need for enhanced visibility and control is transforming how enterprises approach automation. It’s no longer enough to simply automate; applying observability principles to orchestrate critical business processes is essential for achieving operational excellence.

To address this, Redwood Software is introducing a new solution that empowers users to visualize every process in motion, predict bottlenecks and turn uncertainty into opportunity. Today, Redwood announced Redwood Insights, first being integrated into RunMyJobs by Redwood, a market-leading automation solution.

Redwood Insights will deliver:

• Role-based dashboards for operators and administrators
• Orchestration analytics that provide actionable intelligence
• AI features with smart narratives for data views and deeper data exploration
• Analytics and visualizations to identify problems and bottlenecks before they impact operations

Redwood Insights, integrated with RunMyJobs, enables users to visualize every process in motion, predict bottlenecks and turn uncertainty into opportunity. 

Applying observability to workload automation and SOAP offers a path from chaos to clarity. It empowers organizations to achieve autonomous transformation, optimize operations and thrive in a complex digital world.

With the launch of Redwood Insights, Redwood aims to transform automation from an opaque process into a transparent, self-healing ecosystem. By embracing observability and AI-driven insights, you can move from simply managing automation to truly orchestrating business harmony. 

Learn more about how Redwood’s automation solutions and Redwood Insights can help you harness the power of observability and AI to achieve precision, synchronization and harmony in your business operations.

A few people start digging into logs. Someone restarts a job chain manually. Another calls IT. You eventually find the problem: a single failed data transfer between your MES and SAP solutions. One unforeseen connection that didn’t work as expected.

When the production line stops, so does your business. It’s expensive and frustrating. You’re burning labor and missing delivery windows. Not to mention risking customer churn. And it will happen again — not because your team isn’t capable but because some, if not all, of the systems that touch your plan-to-produce value chain were not designed to work together in today’s cloud- and AI-based IT environments.

Why manufacturing is a challenge for IT

Manufacturing operations today generate staggering volumes of data. Sensors, machines, MES platforms, ERP systems, logistics partners — all producing and sharing information in real time. But most manufacturers aren’t dealing with one unified system. You’re working with layers of old and new technologies stitched together with custom integrations and manual workarounds and expecting them to communicate and share information with each other.

These systems don’t share data easily. Every connection requires oversight. Every exchange of information requires orchestration to ready it to move between disparate applications. Every exception needs human intervention. Every upgrade breaks something else.

Instead of contributing to continuous improvement, your best people are stuck troubleshooting and patching. And it’s slowing you down. Or, even worse, creating a bottleneck that shuts down operations.

If you continue with manual workarounds and disconnected automation, you’re risking:

• Inability to balance capacity with demand
• Higher operational costs from inefficiencies and errors
• Lost market opportunities because of slow or missed deliveries
• Customer dissatisfaction due to quality management issues and delays
• Lack of scalability that limits your competitiveness

Moreover, if you’re still depending on manual steps and separate solutions to monitor different parts of the process, these consequences are even greater.

You don’t need more customized automation — You need a central point of orchestration

Automating individual tasks simply won’t help you dig your way out of this. More one-off custom coding and scripting isn’t the solution for systemic inefficiency. What you need is intelligent orchestration: a coordinated framework that connects and synchronizes your data, production processes and systems end to end.

Orchestration is the only way to scale production without compromising speed or quality.

True orchestration replaces the chaos of reactive operations with continuous, autonomous process flow. Executing steps is only the beginning. You also need a setup that inherently understands dependencies, monitors for anomalies and predicts outcomes so you can adapt before it’s too late.

That’s what it takes to win today because your competitors are producing faster, delivering faster and responding faster to market demands. As for your customers? They won’t wait.

Modernizing production planning: Use cases

Here’s what orchestration with an advanced, SAP-certified workload automation platform looks like in practice in your industry.

Material procurement and delivery

You know how fragile material flow can be when procurement is decoupled from real-time conditions on the floor. With the right workload automation solution, you can tie replenishment directly to production order triggers — not batch-based MRP runs or manual and standardized reorder thresholds.

As inventory hits a predefined floor, you can fire off a sequence that checks availability in SAP, generates purchase orders based on contract terms, updates delivery expectations and adjusts planning data across systems. You’re not waiting for someone to notice the shortfall. The system sees it and acts automatically. That means no surprises or production delays caused by avoidable gaps in supply.

Autonomous communications with supply chain partners

Your suppliers and logistics partners need timely, accurate data to do their jobs, but keeping everyone aligned by email or spreadsheet doesn’t scale. Orchestration enables your production plan changes to take place automatically and ripple through your systems and supply chain.

Shift in the forecast? The system regenerates your schedules, flags the impact on material needs and shares updated requirements with suppliers via EDI or secure file transfer. It alerts your logistics teams if the adjusted timeline affects outbound shipments. Everything stays in sync, and you don’t lose time or credibility explaining changes after the fact.

Quality assurance

You already have checkpoints and inspection plans, but they’re only as effective as your ability to act on the results. Orchestration supports quality data, making sure it’s logged correctly and that it triggers the correct response in real time.

You can build workflows that align to an Industry 4.0 framework, where MES outputs feed directly into your ERP evaluation rules. If a reading passes, production proceeds. If it fails, you immediately route the lot for rework, notify QA and update status fields for traceability. With predictive analytics layered in, you can catch patterns, like defects tied to certain equipment or shifts, before they become bigger problems. And you can automate the response, not just the alert.

Data analysis and decision-making

Pulling together data about machine efficiency, order progress and labor allocation takes time. If you were to truly orchestrate the process, you’d eliminate the lag time between when the data is generated and when it’s useful.

Automated workflows can consolidate data across MES, ERP and planning tools to generate live dashboards or exception reports. If a line is underperforming, your planners will be alerted quickly so they can reroute jobs to optimize resource utilization. And if a shift is falling behind, you can reallocate capacity. You don’t have to wait until the end of the day or week to know where things stand.

Protect your SAP clean core while innovating your manufacturing processes

Implementing orchestration doesn’t require abandoning your clean core SAP strategy if you’re in the midst of a cloud transformation and have ambitions to optimize your production operations. The right solution strengthens it. 

RunMyJobs by Redwood gives you the power and flexibility to scale without chaos, extend your SAP innovations without compromise and deliver products faster without cutting corners.

Replace custom scripts and fragile interfaces with robust, purpose-built SAP connectors for SAP S/4HANA Cloud, IBP, APO, Datasphere, Integration Suite and many more. Orchestrate thousands of interdependent processes and workflows across these and many other applications without custom scripting so you can optimize labor, raw materials and equipment usage and reduce lead times. The outcomes? Cost savings and the ability to meet market demand for your products.

That’s how you make every production run efficient, compliant and on schedule — by centralizing orchestration and eliminating bottlenecks between planning, execution, QA and delivery.

Step into a faster, smarter era

Redwood Software has helped some of the world’s top manufacturers modernize their complex SAP environments with automation fabrics.

• Daikin used RunMyJobs to minimize human error and free its administrators to work on higher-value tasks. Customer service improved, as staff could get straight to fulfilling product orders and other logistics requirements instead of having to deal with process failure issues.
• Kaeser’s global orchestration story is another case in point: By consolidating 40+ country-specific processes into a single, automated chain in RunMyJobs, they gained the speed, resilience and flexibility to keep up with demand without expanding headcount.

These aren’t isolated wins — they’re the new standard. If your manufacturing and IT teams are still manually assembling the puzzle of mission-critical processes, you’ll inevitably fall behind those who have figured out how to balance their capacity with demand with fewer resources. 
Choose effortless orchestration to increase production speed while maintaining quality and delivering on time every time.

Book a demo to see how RunMyJobs can help you take control of your production planning and avoid ever having to scramble at 2 AM again.

The latest report from Americas’ SAP User Group (ASUG), ”How to Unlock the Value of SAP BTP,” reveals that “organizations are increasingly choosing to strategically leverage SAP BTP within SAP S/4HANA journeys.”

Notably, 55% of ASUG members now use SAP BTP, and 73% of SAP BTP users are leveraging it for an SAP S/4HANA transformation. These numbers demonstrate that SAP BTP is no longer just an optional add-on but a core component of modern SAP landscapes.

Because of its diverse capabilities, SAP BTP can introduce complexity and additional IT expertise or other resources for executing new innovations in your SAP environment. Even successful companies struggle to make the most of their technology, especially when it encompasses cloud apps and comprehensive solutions like SAP BTP. To truly harness its capabilities, you need a robust strategy for managing and orchestrating the innovations you’re creating across a diverse tech stack.

RunMyJobs by Redwood, the only workload automation (WLA) solution included in the RISE reference architecture, can help you achieve frictionless automation and orchestration across your business activities, applications and data management.

Here, we’ll review insights from the report about which SAP BTP functions ASUG members are prioritizing to help you draw inspiration and plan for using RunMyJobs to optimize all the great innovations you create in SAP BTP.

Under the wider BTP umbrella, the most valuable technologies for organizations using the solution involve integration, analytics and process automation components. 

p. 3, “How to Unlock the Value of SAP BTP”

Integration: Keeping your connections efficient and predictable

69% of SAP BTP users say integration is key.

But page 3 states, “While connecting business applications and data across the enterprise remains the top priority for survey respondents, fewer respondents were able to achieve this benefit compared to 2023.”

This discrepancy suggests you should look for easy integration as a core feature of any complementary solutions you select. RunMyJobs orchestrates complex integration workflows to achieve autonomous integration across SAP and non-SAP systems. Out-of-the-box, purpose-built connectors enhance the efficiency and effectiveness of your customizations.

Let’s say you’re a global manufacturer managing complex supply chain and production processes. 

• You feed customer orders from a third-party CRM solution to SAP S/4HANA Cloud, triggering a series of interdependent processes spanning different solutions for procurement, production and logistics, all connected using SAP BTP Integration Suite.
• While these processes are connected, numerous tasks and activities must be completed to ensure smooth interaction across multiple applications.
• RunMyJobs complements SAP BTP Integration Suite by autonomously orchestrating the necessary steps to optimize integrations built in SAP BTP. It might trigger validations of your bill of materials (BOM) in SAP IBP, automate purchase orders being sent to suppliers via SAP Ariba and kick off notifications to your MES and logistics systems about production and delivery schedules.

Data fabrics: Supporting your key decisions

61% of SAP BTP users name analytics as a top-priority component.

Handling data efficiently and being able to utilize insights effectively is, understandably, a major concern for forward-thinking businesses amidst a cloud transformation. As the report states on page 4, “Data management will be crucial in fully unlocking the potential of SAP BTP.” 

Many SAP BTP users employ SAP Datasphere and SAP Analytics Cloud to simplify data management. Yet, simultaneously using a legacy job scheduler will result in a vulnerable, ironically disconnected environment in which clean core strategies in your SAP S/4HANA system can be compromised.

RunMyJobs schedules, triggers and monitors sequential task chains required to move data across your entire tech stack into SAP BTP data management tools. In other words, your data flows — to and from SAP BTP solutions — are fast, consistent and accurate.

If you’re a retailer, you might use SAP Datasphere to extract, transform and load sales, customer and inventory data from Shopify into an SAP S/4HANA or SAP Analytics Cloud system. To execute this data flow, you must build, schedule, trigger and monitor many individual data movement tasks. Doing this manually is time-consuming and error-prone, but RunMyJobs’ WLA capabilities optimize the process.

Automation: Driving your mission-critical processes

55% of SAP BTP users are focusing on process automation.

It’s not surprising that SAP BTP users are increasingly focused on automation. SAP BTP can automate simple to moderately complex processes. This can relieve teams of the burden of repetitive tasks and activities. On page 5, the report acknowledges, “Embracing automation will drive efficiency.”

But if you’re extending your environment to the cloud, you’ll likely have to build a lot of custom automations. And holding onto a legacy scheduler will saddle you with the burden of maintaining, updating and QA’ing your scripts and fragile endpoints.

Enterprise WLA with RunMyJobs allows you to run and monitor large volumes of background jobs, transactions and highly complex, interdependent processes across your entire IT landscape. Not only can you automate, but you can visualize the process and quickly identify and resolve any errors or bottlenecks. For example, you can streamline the order-to-cash process — importing hundreds of thousands of sales orders at a time from your CRM to SAP S/4HANA for mass credit checks and invoice generation, then processing and matching customer payments. 

AI: Seizing new opportunities 

34% of SAP BTP users cite the importance and value of AI.

There’s no denying that AI needs to be part of the conversation, but as SAP and other technology providers rapidly upgrade their AI models and offerings, it will become more difficult to understand how to fit it into your everyday processes without introducing new frustrations or roadblocks. 

SAP’s AI strategy involves providing tools and services within SAP BTP to enable users to develop and integrate AI-driven features into SAP solutions. This includes access to pre-built AI models, development environments and integration with established AI frameworks.

As a leading automation company with 30 years of experience, Redwood Software takes a cautious and strategic approach to implementing the latest AI technology in sensitive scenarios. Through best-in-class automation practices, RunMyJobs ensures the continuous flow of information feeding SAP AI models is accurate, timely and unbiased across your data pipelines.

What’s your ROI for SAP BTP?

While more users say they can fully leverage SAP BTP solutions (46%) than in the previous year’s report, 33% still say “No.” Integration hurdles, inconsistent data flows, fragmented automation and uncertainty around emerging technologies such as AI can get in the way of extracting its full value. Without the right approach, you could miss out on many of SAP BTP’s advantages and finding its strengths to be sources of complexity instead.

To fully leverage SAP BTP, consider an enterprise-grade WLA platform designed for automating highly complex, end-to-end processes across multiple applications. These processes are long-running, handle high transaction and data volumes, operate on strict daily timelines and are mission-critical. Failure can put your entire business at risk. 

RunMyJobs can schedule those processes, such as data backups, batch processing, file transfers, workflow approvals, monitoring and more across many different transactions, systems and technologies.

Explore more about how to increase the long-term value of your SAP investment with an SAP-certified partner that co-innovates with SAP.

The dual pressure to integrate multiple cloud computing environments with business and IT systems while implementing new technologies, such as artificial intelligence (AI), makes it challenging to meet evolving business requirements while simultaneously addressing resource constraints and filling skill gaps across new and legacy systems. 

These elements struggle to co-exist harmoniously, leaving your team mired in troubleshooting issues while attempting to integrate new technologies. To enable transformation without impacting business services, you must adopt a strategic approach to scaling your IT workload management.

Read on to explore IT workload automation as a solution — its applications in a Service Orchestration and Automation Platform (SOAP) capacity and a step-by-step guide to using it to scale effectively.

Gartner SOAP Critical Capabilities: IT workload automation 

In its 2025 Critical Capabilities for SOAPs report, Gartner® spells out five top Use Cases for these advanced workload automation tools, one of which is IT workload automation. According to the report, this use case is defined as the “automating planning, execution, management and reporting of IT workloads across enterprise systems.”

An IT workload is any program or application that runs on a computer — anything from a simple script to move some data around to a complex chain of tasks in a remote system (e.g., SAP ERP, AWS, Databricks or Informatica). A SOAP that successfully automates these functions must enable teams to:

1. Plan: Assess IT processes to identify those with high impact for performance and reliability improvements from automation.
2. Define: Map processes to workflows, set schedules, establish run and failure conditions and align them with service-level agreements (SLAs) and business outcomes.
3. Execute: Implement workloads according to predefined parameters.
4. Manage: Oversee IT operations, adjust for performance and resolve issues.
5. Report: Generate detailed insights to guide ongoing optimization.

IT processes: Quick wins for targeted scalability 

To fully capitalize on the opportunities offered by an orchestration platform, it’s important to know which processes are most suited for scaling. Depending on your current resource availability and the potential impact on your business operations, you may prefer to prioritize the simplest processes first.

Look for:

• Tasks that span multiple systems. Coordinating these can deliver efficiencies and reliability improvements. Perhaps identify achievable but challenging hybrid cloud processes or ones that span on-premises and SaaS cloud services to build on for future phases.
• Tasks that are dependent on business events. Connecting IT and business systems with workload automation means activities happen more quickly from the end-user’s point of view. Starting with IT services that are triggered in a customer-facing system can deliver demonstrable benefits in early phases.
• Tasks that are interdependent or have complex dependencies. Verifying that all the pieces are in place maximizes the likelihood of success. Workload automation allows us to do this using methods that align with skills and other solutions, reducing technical debt. Choosing tasks that often fail due to dependency on employees can show immediate benefits and are incredibly cost-effective.

The following examples are in order from simplest to most complex:

1. Backup and archival of data from across the business
2. Setup for new employees or customers across different systems
3. Automatic scaling of cloud environments up and down during company downtime
4. Disaster recovery replication management, ensuring all requirements are met
5. Data center management, managing control of physical and digital systems
6. Disaster recovery testing and activation 

Automate your way into the green: How to scale IT workloads

While there will be some variation in how you pave the way for growth and efficiency, here are some general guidelines if you’re not sure where to start.

1. Assess your current automation landscape

The first step is to perform a thorough audit of your existing automation environment. Begin by identifying solutions with automation capabilities, stand-alone automation tools, resource-intensive tasks, critical dependencies and workflows that have high latency or delays between steps.

Then, determine key performance indicators (KPIs) to establish a baseline. For example:

• Automation success and failure rates
• Process completion speed
• Manual intervention and labor costs

Or, more specific to your processes, considering our examples above:

• Data restoration request response time?
• New employee request resolution time?
• Reduced cloud computing costs?
• Disaster recovery failover testing success rates?
• Time to shut down an on-premises data center for maintenance?

Potential challenges at this stage: You may have to tackle outdated scripts and grapple with fragmented tools. Without centralized visibility, you’ll also likely face insufficient monitoring. 

Note your issues early to lay a solid foundation for the upcoming steps.

2. Build a scalable IT automation strategy

Once you’ve assessed your current automation stage, it’s time to define a true strategy for scalability. 

• Set clear, measurable goals. Do you want to reduce manual interventions by 50%? Cut job failure rates by 30% within six months?
• Prioritize high-impact cloud workloads. Focus on those that:
  • Often involving file transfers or high-volume, repeatable jobs
  • Require batch processing power
  • Cloud resource management
• Configure your workload automation for load balancing. Distributing tasks evenly across your available resources gives you the best chance of preventing bottlenecks as you take on increased demand.

3. Manage and monitor workloads in real time

Effective real-time management is essential when scaling. Dashboards can give you instant visibility into job statuses and system health. Alerts are also key for being able to rapidly respond to issues despite an increase in volume.

Set up automatic failure recovery protocols, such as job retries, failovers and escalations, to maintain continuity even when issues pop up.

The insights from your real-time monitoring are only as valuable as what you do with them. Take quick action when it becomes clear you need to adjust computing resources or dependencies to streamline execution.

Keep in mind that real-time workload management isn’t a one-and-done process. Continuous adaptability is what will make your automation efforts successful.

4. Report on and communicate automation successes

You need support from your entire leadership team and all stakeholders to keep up with the backend needs that support changes in the business. IT scalability contributes to broader business growth, but this correlation is not clear to everyone.

This means generating comprehensive reports that highlight the business impact of IT process automation. How have your workload adaptations contributed to greater efficiency in routine tasks, improved service delivery and/or a better customer experience?

If you can also use your data to help forecast your needs, you’ll be more likely to expand quickly with new automation tools and integrations, which will allow you to handle even more complex workflows and perhaps support new services. Scalability could be a self-perpetuating cycle!

Why a ranked SOAP solution should be your scaling companion

More than just running scheduled tasks, you need to strategically orchestrate automated processes to ensure your operations continue to be error-free as you grow. A SOAP solution, especially one that’s been named a Leader in the 2025 Gartner Magic Quadrant for SOAPs, is an indispensable partner along this journey.

With a Redwood Software solution, you’ll get:

• Centralized control
• Measurable efficiency gains
• Unparalleled adaptability
• Easy enforcement of compliance and governance

Redwood ranked #1 in all five Gartner Critical Capabilities Use Cases for SOAP in 2025. Download the full analyst report to find out why and envision the resilience you could achieve with all types of workloads by using a leading SOAP solution as you scale.

We might be discussing aggregating long-term sales figures or reconciling stock and inventory with customers, but those are ways of talking about the business rules that we apply on top of data management processes.

In many organizations, the departments that define those rules own some of the process of moving or manipulating data. Other teams collect their data — the raw sources — and use it for their distinct purposes. Centralized teams work to manage sources of truth in major business apps or master data repositories, and a myriad of data sources exist at the edge. Point-of-sale (POS), remote office and legacy systems add to the potential chaos of separate but interconnected flows of data.

Although some teams may feel their part of the flow is under control, others are re-running processes, modifying data manually to allow other processes to work or resorting to collecting raw data to reach their goals.

As the complexity of data increases, the reality of not having complete control over the data pipelines that run the modern business becomes more and more of a threat.

Data: “The new oil”

We all agree: Data is one of the most precious resources for today’s enterprise. It drives new industry as oil once did. We can extend this analogy to data management — it’s the critical refinement process, without which data is largely worthless.

This analogy is useful if we consider an oil pipeline diagram. With the extraction, refinement, transportation and consumption of those refined products, there are many parallels with data management pipelines.

While the oil pipeline starts with the flow of mostly one type of thing, data pipelines start fragmented, coming from tens, hundreds or even thousands of different sources. Data, therefore, presents an exponentially larger, more complex problem than the pre-treatment of crude oil before it enters the refinement process.

A critical part is missing in our pipeline analogy that affects everything else: the creation of the data. Data pipelines start with business activities, interactions with customers, apps, points of sale, Internet of Things (IoT) and more.

Old-school posters may have shown the natural processes that created the oil, but unlike the geological speed of those processes, our valuable resource is being written, re-written and consumed in seconds, and the inputs to our process are chaotic, unruly and spread out.

Blockages in data pipelines

A data pipeline is a complex web of data sources, logistics and analytics processes that underpin business operations.

This web may look like it was made by a drunk spider in some organizations, characterized by fragmented and siloed data sets and solutions. If this sounds familiar, you’ll likely perceive data management as laborious and error-prone.

Without a cohesive automation strategy, many IT and data management teams encounter the following struggles.

• Waiting for other teams to do their part of the process. This delays downstream activities, especially if different teams have different ways of sharing data and information and managing the scheduling of tasks.
• Vendors or departments changing data formats. You may need to reconfigure multiple scripts, fields or tools that impact many tasks.
• New technology requiring a new method or skill. Data management tasks may rely on technology that uses a different protocol or standard than what your business has used thus far.
• Managing multiple automation tools with narrow use cases. If many business systems are using their own schedulers and automation services, tool sprawl can be a major time sink for your IT team.
• Teams manually unpicking changes to data sets. This makes it cumbersome to run the same process or script again in the next data management step.

All these issues affect the quality, compliance and timeliness of data used in decision-making.

Drilling for data

Distilling data into actionable insights that drive business operations and decisions also reflects the same basic steps that we see in the oil pipeline analogy.

Extraction

Collecting data from all sources at the right time and coordinating its delivery downstream to the next stage is no small feat. There are many tools for collecting data, and some teams use bespoke scripts and niche solutions.

Refinement

Once extracted, the data is manipulated and analyzed to make it more useful for different processes and tasks. New data sets may be created with different values, conversions of data formats or standards and different types of analysis to perform calculations and correlations.

Transportation

Lastly, data is loaded into destination systems and delivered to the end consumer or used in other processes.

The above stages align nicely with a commonly discussed data management process: Extract, Transform, Load (ETL).

Organized chaos

To move from data chaos to data clarity, it’s vital to understand the difference between data management techniques and data management processes.

We’ve been using some terms associated with data management so far, such as ETL. Using that and two other relevant examples, this table explains where they fit into the data management function and the oil analogy that’s been serving us so well.

How data sources impact the pipeline

To further bring order to the fragmented chaos we often see in data management, we need to also look at sources of data and understand how they play a part in the whole.

We can categorize data sources in many ways. The diagram below looks at each system’s significance to business processes — versus how close to end-users, customers and the edge of the business system architecture it is.

At the bottom left, we see data stores and hosting for customer-facing apps and back-end processes.

These systems likely have built-in automation capabilities, but they’re either narrow in focus or shallow in capability to integrate with other systems. 

The right automation solutions can govern and manage automation in this section, ensuring tasks take place at the right time and dependencies are managed.

In the middle, we have middleware, pure data storage and analytics.

These systems sometimes have a limited set of automation capabilities. They integrate well with the systems on the bottom left but may struggle with the complex data sets coming in from other systems towards the top right.

At the top right, you’ll find end-user tools and productivity apps.

Often a data destination and a data source, end-user control creates problems for data integrity and availability.

And a special mention: embedded solutions.

These are the out-in-the-wild systems, such as IoT and POS. They’re often legacy systems that can be specific and problematic to deal with, especially in the event of a failure. Data sources are often spread out with data sets per device or location.

Data tends to flow from embedded solutions and business apps into middleware and business systems before being sent back to business apps, end-user tools and reporting apps.

Springing a leak

With parts of the processes spread out across tools, governed by one system or team, gaps and cracks start to appear. In those cracks, data management processes unravel in frustrating ways.

A robust automation strategy allows us to design seamlessly integrated, efficient data management processes. If errors do occur, you can build in logic and pre-configure reactions to problems, allowing your data pipeline to progress and repair without laborious unpicking and troubleshooting.

Workload automation’s broad capabilities to automate every stage of the pipeline means all the disconnected activities can be joined up — the end of one step flows immediately into the start of another with maximum efficiency. In the event that errors occur, you can build in logic and pre-configure reactions to problems that allow the data pipeline to progress and repair without laborious unpicking and troubleshooting.

By reliably automating business-as-usual processes, your team can take on higher-value and more interesting tasks instead of just keeping the lights on. With end-to-end automation, it’s common to experience increased velocity, more reliable input for key decisions and peace of mind around data compliance.

Discover how RunMyJobs by Redwood can bring clarity to your data management processes: Book a demo.

It’s also more important than ever. Keap reports that the average ROI of investing in customer experience (CX) includes a 42% jump in customer retention, a 33% increase in customer satisfaction and 32% more cross-selling and up-selling. 

Yet, CX quality is at an all-time low, according to Forrester’s 2024 US CX Index. That could be because companies are finding it harder and harder to identify and manage all the components that drive CX today, which are no longer limited to your front-end training or the friendliness of your support reps. The CX story begins with the information these reps can access — quality back-end data.

Let’s examine why a stable, high-quality CX may be hard to achieve by today’s standards and how automated data management as part of an automation fabric can drive better outcomes.

Why organizations struggle to provide superior customer service 

Delivering exceptional customer service across a large enterprise comes with unique challenges. In both everyday calls and high-pressure situations, you need real-time information. Whether your customers call in with questions about order fulfillment and delays, mistakes on a bill, or duplicate or failed payments, they expect immediate answers.

Before considering how to get your business to a place where you always have that information, we’ll cover the most common things that can impede the pathway to a strong CX.

Data silos and integration issues

Disparate systems often fail to communicate effectively. Fragmented data makes it difficult to acquire comprehensive insights that support customer interactions. For example, a customer service rep may have to check multiple systems to piece together a customer’s order history, leading to delays and potential errors.

High volume of customer inquiries

Large numbers of inquiries can overwhelm your team and extend response times if you don’t have the proper workflows to support accurate routing. During peak seasons or promotional periods, your volume can surge and put even more strain on your resources, almost guaranteeing a dip in service quality.

Out-of-date information

Your data must be stored and processed consistently and accurately so you can provide the answers your customers want on the spot. Data lags can slow down customer service operations and create confusion about what’s true and when team members made changes.

Slow systems

Sluggish technology can be a significant roadblock to CX. If your systems lack the capability to handle modern customer demands, they can get in the way of your team providing timely and efficient service. Upgrading to faster solutions is often costly and time-consuming, so you could find your customer service function stuck in a cycle of inefficiency.

Human error

Manual data entry and retrieval processes are prone to mistakes. Even the most diligent employees can make errors, which can cascade and cause the dissemination of incorrect information to your customers. Humans will always be unpredictable, so your technology needs to be reliable to counterbalance this risk. 

Resource constraints

Staff and budget constraints can also hinder your ability to maintain high service quality. Even with optimized processes, insufficient human capital or financial resources can keep you from delivering the quality of service your customers expect.

Industry-specific challenges

Creating a top-notch CX can be an even bigger job when you consider your industry requirements. Below are just a few examples of additional complexity.

• Manufacturing: Supply chain delays or disruptions in the procure-to-pay process can greatly impact product availability. If a key component is delayed, your entire production schedule could be thrown off. The outcome? Backorders and unhappy customers.
• Retail: Managing the logistics of returns and exchanges without accurate and real-time inventory data can lead to chaos. Customers are frustrated, employees are confused and the long-term decrease in loyalty is measurable.
• Utilities: Complex billing structures, usage patterns and variable rates make customer service particularly hard in this industry. You may not be able to answer billing inquiries with a simple lookup, and a small error on a statement may require a disproportionate amount of time and effort to resolve without automated systems that speak well to each other.

The impact of addressing these and getting issue resolution right is clear: 80% of customers feel more emotionally connected to your brand when you successfully solve their problems. 

Unsuccessful approaches to perfecting CX

Many companies implement superficial measures at the customer-rep interaction level to circumvent all of the above obstacles. They may adopt a new CRM, better call center software, a chatbot or a voice assistant.

While these can increase speed and offer the illusion of attentiveness, they do not guarantee that a call center team will be able to get the right data sets from the right systems at the right time. They’re only as effective as the data they’re being fed.

Automation fabric: The ultimate data management solution

Addressing the data behind your CX requires more than quick fixes. You need a data management ecosystem — an automation fabric — that supports end-to-end process automation across different data sources and systems.

A perfectly integrated tech stack ensures your systems communicate effortlessly. You never have to worry about the silos that often impede customer service. Inquiries can be resolved in seconds, and account history, inventory details and more are all available in a single interface.

One critical piece of automated data management is how you approach extract, transform, load (ETL) processes. Your data must be in a usable format and loaded into the appropriate systems for it to positively impact the front-end customer service side. Automating ETL tasks can speed up your data processing and reduce the risk of errors that often accompany manual data handling. For example, in a retail environment, automated ETL processes update inventory levels so customers get accurate information about out-of-stock items.

Build your fabric with a workload automation solution

Well-executed data management isn’t just about access; it’s about how well you collect, copy, move, manipulate and cleanse the data before your customer service professionals use it and offer it to your customers.

But data management pipelines are fragile. One wrong command, field or trigger can input a surge of bad data into your records. If you try to connect multiple automation tools and various data solutions, you’re at greater risk for these difficult-to-remedy cases, which could impact many customers at once.

A workload automation (WLA) solution can be the linchpin, bringing all these data management elements together. WLA goes beyond basic automation to harmonize and orchestrate your data and create a single source of truth. 

The value of WLA lies in its real-time data integration, validation and monitoring capabilities. A WLA platform orchestrates data across all systems, integrating your data warehouses, ETL tools and data sources. Continuous monitoring and management with powerful conditional logic, predictive SLA and data management integrations ensure smooth operations and, therefore, reliable CX. 

How WLA solutions address CX hurdles

Automating end-to-end data processes provides insurance for you and your customers, protecting you against the negative outcomes of slow systems, data silos, human error and more by generating:

1. Low failure rates: Automated systems experience fewer data-related issues than those driven by manual input.
2. Reduction in human labor costs: Automation frees up your team to focus on more strategic — and revenue-generating — tasks.
3. Scalability: Top WLA solutions can scale with your data management needs to accommodate growth and complex workflow changes.
4. Improved data quality: Consistent attention to data on the back end means the data that reaches your customers is thorough and accurate.
5. Increased efficiency: Automation streamlines data processes to optimize efficiency and enables your team to serve customers with less stress and fewer steps.

RunMyJobs by Redwood boosts customer satisfaction

The benefits of transforming data management processes are clear in the stories of Redwood Software customers. 

Anglian Water generates 16,000 invoices per day, but issues with its overnight billing processes were causing overruns and stressing its systems to the point of failure. Thanks to the increased efficiency the company achieved with RunMyJobs, Redwood’s workload automation solution, and the resulting call center consistency, it’s now ranked #1 on the Ofwat water regulator service incentive mechanism (SIM) table.

Want to follow suit? Book a personalized demo of RunMyJobs to learn how to implement an automation fabric, improve your data accuracy and build a winning CX.

While we’re focusing on these concepts in business and reading about them in the news, many of us are still looking to the future — for a revolutionary moment to come along in AI or for it to get just that little bit better.

The latest advances in AI and machine learning mean we have many opportunities now to improve work and play. Specifically, reducing the resource burden of low-value or time-consuming tasks and enriching processes with natural language analysis and content. There are readily accessible benefits that organizations in various industries have yet to realize.

Machine learning vs. AI

Machine learning (ML) is sometimes seen as a precursor to AI, but it’s still part of the whole AI picture and is highly relevant today. Though largely unseen by end users, ML is built into many software products we already use. 

Using ML to train models to recognize patterns and anomalies is the most common use case today. In automation, this surfaces in the infrastructure needed for large-scale training. Services such as AWS Batch provide easy ways for AI developers to train models.

The search for more generalized forms of ML models brought us to the current phase of AI development.

Where AI is now

Generative AI and large language models (LLMs), such as OpenAI’s ChatGPT, offer a human-friendly way of interacting with the most recent models. While this makes them feel much closer to the “real” AI we imagine, in most cases, the capabilities we can reliably and confidently use are relatively narrow.

As part of a workflow, these pre-baked models can quickly summarize information and bridge the gap between workflow and employee. The information you ask a model to summarize could be about the workflow itself or the process the workflow is automating.

Remember, to get a desired and consistent output, we need to be specific in our prompts.

Foundation models and “AI PaaS” services are pre-trained and often tuned for a specific purpose. Businesses looking to use AI models need to train them with data from business processes. Examples are Amazon Q and Amazon Bedrock.

Solution enhancements to technology using AI models are common, but with the new wave of AI technologies, we can expect many solutions to provide a more human interface for accessing knowledge and information. 

AI workflow automation potential

End-to-end process automation depends on an integrated framework that seamlessly connects automation tools, processes and data sources—an automation fabric. AI complements automation fabrics in the form of built-in features or connectors that facilitate greater process efficiency and accelerate business outcomes.

Putting the more novel or complicated advancements aside for now, let’s dig a bit more into how implementing AI-powered workflow automation can bring the benefits of AI and LLMs to your routine tasks.

What’s possible with the ChatGPT connector for RunMyJobs

We’ve built a ChatGPT integration for our workload automation solution, RunMyJobs by Redwood, so AI can further the platform’s value of unleashing human potential. For many uses, ChatGPT exists alongside workflow steps as a supplement or a way to interface with users. In some cases, it can replace existing steps or manual tasks users may do later.

Using the ChatGPT connector and job template, adding a prompt with information from a workflow is simple and works like any other step in a chain.

As with the user interface for ChatGPT, you can send data as a chat via API. The connector enables you to configure the prompt you’re sending and use that in your workflow. Effectively, you’re sending ChatGPT a question and getting a response and can optionally maintain the history for a contextual conversation. You can extend this functionality and pull information in from any source using other connectors and scripts.

Let’s talk about how organizations are expanding the power of RunMyJobs with ChatGPT.

Crafting emails

Emails and other writing needs are some of the most common reasons people currently use tools like ChatGPT. Given the immense library of previously entered content the app can draw from, it does an excellent job.

In an automation context, you’d be likely to send an email when a job is starting or has been completed. The email might simply notify, or we might embed some data, times or other information. The problem is that original formatting may break down, the data can be missing or changed in a way that affects the legibility of your email.

In RunMyJobs, you can collate a set of information using workflow parameters and other data, send that to ChatGPT and ask for an email summary, and then use the output to craft your email. You could store the data in a RunMyJobs — in a data table or parameter — or in a separate file the workflow can access.

Alternatively, you could maintain a conversation with ChatGPT: Each time a workflow progresses, you’d send a new piece of information, the time the given step was completed and the outputs to ChatGPT. At the end of the process or upon an error, it can provide a summary of events so far.

You could also send ChatGPT other information: Structured data like CSV lists or unstructured data like emails that the workflow handles as part of its processes, asking for summaries or specific queries about the data to send to users in emails. See more examples in the upcoming sections.

⚠️ Although it’s interesting to have a conversation with the AI chatbot throughout the workflow, and it can be used for ongoing enhancements, I have to point out that the latter method could be quite expensive in terms of API calls.

Quick translations and extracting text

In many use cases, you might be handling documents, emails or other data that’s in a language other than your main business language or is unstructured in nature.

Here, it’s a good idea to think about the criticality of the translation or extraction. The benefit of using ChatGPT or another general model to do this is you can instruct it generally on what to do. The downside is that leaves some room for a variable, or changing, response.

When dealing with emails or other forms of non-critical communication, we could use ChatGPT to make a quick translation pass to help any users who need to assess the data later.

Or you might need to handle a dataset with comments in a different language; you could pass comments selectively to ChatGPT for translation.

We could also ask ChatGPT to extract specific portions of text, perhaps looking for countries, place names or other recognizable information to include in a summary report or an email.

⚠️ It’s worth remembering that while ChatGPT is capable of producing translations, the model hasn’t been fine-tuned specifically for translation tasks. For critical or professional translation needs, it’s generally recommended to use dedicated machine translation models or services designed explicitly for translation.

Interpreting and summarizing data

Data analysis is a huge undertaking, so it’s particularly valuable to acquire a quick summary or identify something specific from a given dataset. Sending a question to ChatGPT could be the answer. But to do so efficiently, it’s key to learn proper prompt engineering and balance specific instructions with simple language.

A note on data security

To secure your business data while using the ChatGPT connector for RunMyJobs, you should use your own instance of ChatGPT through ChatGPT Team or ChatGPT Enterprise. This will mean your data is kept separate, though still sent to the OpenAI cloud platform.

Your organization may have policies and processes in place to remove or mask personally identifiable information (PII), but even with some data removed or anonymized, you can still ask useful questions to make decisions or share information with other people.

In a workflow handling invoice or sales data, you might anonymize the data and send a list to ChatGPT and be able to ask some specific questions — like our earlier example to look for outstanding invoices. Or, you could ask it to produce summaries of the data to push quick insights to other teams via email rather than them needing to access reports when they have time.

At the most simple level, we could ask for “a short summary of this invoice data” and receive an output similar to what’s shown below to use in an email.

Generative AI for more efficient orchestration

Even if AI is not quite yet an omnipotent being, you can start weaving ChatGPT and other AI-powered tools into your workflows to enrich and streamline processes, save time, give your team members additional insights and speed up decision-making.

If your organization is already using generative AI to a significant degree, there may be more integrated ways to enhance your workflows. A model that understands more about your business could answer specific and unique questions to help you achieve intelligent process automation.
And remember, the ChatGPT integration is just one way to incorporate AI into your workload automation with RunMyJobs and a familiar user experience.

Connecting to other AI systems via REST API is easy with the Connector Wizard.

If your organization is a cityscape, SAP BTP is the urban planner bringing innovative ideas to the table and ensuring everything works together seamlessly. But as any seasoned city planner would tell you, the most impressive cities don’t just look good — they also function efficiently. 

A diverse IT landscape (your growing city) requires enterprise workload automation (WLA) that includes sophisticated job scheduling on top of advanced data management and analytics, no-code and low-code application development and artificial intelligence. WLA tools handle complex workloads, and job schedulers submit the jobs and batch processes autonomously to servers for execution. Together, these power your mission-critical business processes like a city transit system that never sleeps.

Leveraging the combination of SAP BTP and a robust WLA solution is the key to keeping your city’s heart beating.

We’ll discuss the needs that arise from size and complexity, why an automation fabric complements innovations built with SAP BTP and how to take advantage of end-to-end automation as you move to the cloud via RISE with SAP.

The complex needs of an enterprise

When you’re dealing with a large number of highly complex and interdependent activities, tasks and jobs, you need every one of them to execute perfectly today and every day. There are a few factors that make your automation needs unique compared to a business that can rely on basic automation.

Sequential workflows

In an enterprise context, many sequential workflows must run without a hitch at all times. Rather than simple task lists, your organization likely needs to set up complex sequences where the output of one process triggers the start of another. If any of these workflows fails, the whole end-to-end process comes to a screeching halt, resulting in significant revenue loss, poor customer experiences and other negative business outcomes. It’s important to streamline these sequences, preempt process failures before they happen and reduce the error inherent in manual handoffs for a more predictable and reliable IT environment.

Reliable data orchestration

Data is the currency of the digital economy, and its orchestration is about much more than the simple management of bits and bytes. The right data must reach the right process at the right time. Data flows are vulnerable to bottlenecks, so their orchestration can be a catalyst for improving efficiency. Effective data orchestration ensures your data is accurate and available in a timely manner or even real time.

Scalable end-to-end processes

As your company grows, so do your processes — both in intricacy and scale. Resilience is being able to handle an increasing workload without compromising efficiency or performance. When your operations are truly scalable, you can expand service offerings in your lines of business and create new, innovative business models without overburdening your systems.

Global visibility

The larger your organization and the more complex your business operations, the more important visibility becomes — and the harder it is to achieve. Every stakeholder needs to be able to manage and monitor the tasks and stages of work relevant to them. More importantly, leadership must have broad oversight to facilitate strategic decision-making and quick problem-solving.

Enhancing the automation power of SAP BTP

SAP BTP solutions beautifully support automation. They can perform basic job scheduling, and your IT team can integrate with and create cloud applications using ABAP. However, this approach requires significant resources to develop and sustain the complex end-to-end automations many enterprises need.

To equip your IT team and data professionals with advanced automation, integration, observability and governance, a 100% SaaS-based WLA platform that offers SAP S/4HANA Cloud and RISE-certified integration can be the ideal partner solution.

Differences between RPA, BPM and WLA

Across the SAP BTP landscape, you’ll find opportunities to apply robotic process automation (RPA) and business process management (BPM). 

RPA excels in automating repetitive, rule-based tasks that mimic human actions, making it ideal for straightforward activities with little variability. BPM centers around identifying operational improvement opportunities, modeling a business process, defining workflows, automating individual process steps and monitoring process performance for insights. Both RPA and BPM are excellent technologies aimed at automating simple to moderately complex human and machine tasks and individual processes.

WLA, on the other hand, focuses on automating an accumulation of high-volume activities, tasks, jobs and end-to-end processes across an organization’s entire IT infrastructure. It spans many different transactions, systems and technologies and involves scheduling highly complex, interdependent processes such as:

• Data backups
• Batch processing
• File transfers
• Job scheduling
• Workflow approvals
• Monitoring 

Applied to both IT and business processes, WLA can coordinate tasks with interwoven time- and event-driven dependencies. 

Workload automation complements SAP’s existing automation offerings

For optimal operational efficiency, organizations should aim to reduce silos and build a cohesive, integrated framework of automation tools — an automation fabric — using WLA along with SAP BTP.

Optimize your SAP BTP digital innovations with:

Your WLA solution should complement SAP BTP with:

• A full catalog of out-of-the-box, purpose-built connectors to enhance the efficiency and effectiveness of integrations, customizations, data management and analytics developed in your SAP BTP environment, including:
  • SAP Integration Suite
  • SAP Datasphere
  • SAP Data Services
  • SAP Analytics Cloud
• Autonomous integration across SAP and non-SAP systems for scheduling and managing jobs, background processes, high-volume transactions and other tasks within their entire SAP landscape without any manual intervention. Even for the most complex end-to-end processes, autonomous integration optimizes communication, workflow and data exchange between SAP BTP solutions and other systems. 
• Data movement and report execution that schedules, triggers and monitors sequential task chains required to move data across the entire tech stack into SAP Datasphere and SAP Data Services. This ensures fast, efficient, consistent and accurate outcomes in your data flows to and from SAP’s data management tools. 
• Secure data quality as the foundation for SAP AI use cases. SAP’s AI strategy involves providing tools and services within SAP BTP to enable users to develop and integrate AI-driven features into SAP solutions. This includes access to pre-built AI models, development environments and integration with established AI frameworks. Best-in-class enterprise automation practices connected to AI models within SAP allow for the continuous flow of accurate, timely and unbiased raw manual inputs across the data pipeline.

The clean core advantage

WLA is only truly complementary to SAP BTP if it’s implemented in alignment with SAP’s clean core approach. You should be able to extend the functionality of your SAP products without compromising efficiency and agility with unnecessary and resource-heavy customization.

In SAP BTP, cloud compatibility is a major factor in maintaining a unified environment, as it allows ERP code to remain untouched no matter the extensions and pre-built integrations an organization uses as it migrates to the cloud and thereafter. SAP chooses partners that support its clean core philosophy, especially those that make it easy to transition to S/4HANA Cloud. 

Ensure consistent outcomes across your tech stack as you RISE

If you’re in the midst of or considering a cloud transition via the RISE with SAP program and SAP BTP, it’s important to speed up your time to value. The answer is WLA.

You shouldn’t go with just any automation solution; you need one that’s guaranteed to work smoothly alongside SAP BTP. With RunMyJobs by Redwood, you get out-of-the-box SAP BTP integration and connectors that offer:

• Autonomous communication across SAP and non-SAP systems
• Sequential task chain schedules, triggers and monitoring
• Secure data quality
• Fast, efficient and accurate data management
• A continuous flow of information feeding SAP AI models
• Orchestration and monitoring of complex end-to-end processes from a single pane of glass

Like an adept city planner anticipates growth, it’s time to explore the dynamic automation that can level up your SAP BTP environment. Find out more about how RunMyJobs can increase the long-term value of your SAP investment.

It’s no different at work. Checking revenue, checking budgets, checking business strategy — we need to know these are safe and secure as well. 

Thankfully, we no longer have to focus on hunting prey or finding shelter in the modern world, but that desire to check and feel safe is intrinsic to being human.

When it comes to transferring files and data, both internally and externally, the anxiety can be constant. Technology makes this more manageable, and automation goes a step further by removing that mental load from our minds completely. 

However, checking every sent and received file isn’t feasible, especially when you need to do so for hundreds or thousands of files a day. Sheer overwhelm at the volume means there could be thousands of file transfer processes occurring within your organization without regular oversight. You might receive an alert when something goes wrong, but the fact remains that sending and receiving files is a constant vulnerability, akin to a castle letting down a drawbridge.

What if you didn’t need to view file transfer as a liability to be resolved? What if these files were built into your daily processes and automations? 

Managed file transfer (MFT) does just that. MFT is a file transfer management solution adept at keeping your “castle” safe while improving file transfer security and process efficiency. 

Here, I’ll tell you the story of the impact of seamless file transfer and encourage you to write your own.

Chapter 1: Why the file transfer journey matters

Savvy businesses leverage automation to get more work done with fewer resources. Prime targets for automation using workload automation (WLA) tools tend to be internal processes like reporting, ticket management, CRM updates and more. 

However, file transfer processes don’t only take place within your organization. It becomes challenging to easily automate, see and control external tasks like paying vendors, receiving invoices from suppliers and orchestrating other touchpoints in a supply chain. 

Bridging the automation gap between internal and external using an MFT solution not only improves efficiency but also affords your organization other valuable benefits. 

• Easier compliance: If compliance is a major concern in your industry, you’ll benefit tremendously from an MFT solution with built-in features to help you comply with regulations such as GDPR, HIPAA and SOX. You’ll be able to confidently provide secure data handling, audit trails and more in accordance with legal and regulatory requirements.
• Long-term expansion: Communicate securely with a wider variety of external entities regardless of the file sharing protocol they prefer or require. As you scale, you can easily integrate file transfers into existing workflows without the need for reconfiguration.
• Reliable logging and comprehensive reporting: A solution with detailed activity logs provides insights into the performance and efficiency of your file transfer operations. Reports can help you monitor usage patterns and optimize workflows to maximize efficiency. 
• Robust data encryption: Encryption, both in transit and at rest, protects sensitive data from unauthorized access. When you’re transferring files externally, it minimizes the risk of data breaches and ensures that information remains confidential.

What would daily processes look like using integrated WLA and MFT, and how can they help you achieve full end-to-end business automation?

To envision what’s possible, we’ll look at two examples of how businesses use these solutions as part of their tech stack to automate file exchange and protect essential data.

Chapter 2: The purchase order story

In this scenario, let’s imagine a manufacturer called Acme Scooters. They have a contract to fulfill a massive order of scooters for a new school district’s physical education program. Acme Scooters works with their supplier, Wheels Limited, to ensure they have the parts they need to deliver completed scooters on time. 

To keep themselves organized, Wheels Limited uses three integrated and automated software solutions: JSCAPE by Redwood for MFT, RunMyJobs by Redwood for WLA and SAP for enterprise resource planning (ERP).

We begin our journey at Wheels Limited, which just received a purchase order (PO) from Acme Scooters via one of JSCAPE’s protocols. This File Upload event triggers an automation for JSCAPE to send the PO to RunMyJobs.

RunMyJobs processes the PO and sends its data into Wheels Limited’s SAP instance. The data is processed, and SAP generates a purchase order acknowledgment (POA). SAP then forwards the POA to RunMyJobs, which passes it back to JSCAPE. The POA is returned to Acme Scooters via JSCAPE, confirming the order has been received. 

Wheels Limited gets to work building the custom wheels needed for the new scooters. Once they’re produced, RunMyJobs generates a shipping document stating that the parts are ready to be shipped. JSCAPE shares the shipping document file with Acme Scooters while RunMyJobs works with SAP to automate the invoice creation. RunMyJobs receives the invoice from SAP via its integration and leverages JSCAPE to share it with Acme Scooters. 

At every step, automations escort the files where they need to go, with JSCAPE’s event-based triggers facilitating the file transfer across all the software solutions, enabling easy internal file-sharing automation and secure file transfers to external partners. 

Chapter 3: The order-to-cash story

As Wheels Limited and Acme Scooters aim to continue working together, they decide to share a Dropbox account to store and retrieve business-related files easily. 

Acme Scooters, now the premier provider of scooters for K–12 schools, uploads an order to Dropbox. Due to an event-based trigger, JSCAPE recognizes the File Upload event and ferries the order directly into RunMyJobs. RunMyJobs extracts the data in the order, including customer information, and checks it against their ERP solution, SAP. 

The data matches, which allows the automated order process to continue and enables an invoice to be sent back to Acme Scooters. RunMyJobs retrieves a generated invoice from SAP, then passes it to JSCAPE. As the file transfer solution, JSCAPE automatically moves the invoice file into the shared Dropbox for Acme Scooters to pick up and pay later. 

As you can see, the cross-functional integration of an MFT solution with a WLA solution kicks off processes after they’re triggered by external partners without requiring human involvement. Existing tools, such as Dropbox, fully integrate into the automated flow.

Chapter 4: Peace of mind beyond your four walls

Acme Scooters and Wheels Limited may be fictional businesses, but the challenges and complexity they face are very real. Enterprise organizations like these — and yours — are responsible for protecting vast and sensitive data transfers every day. By automating these vulnerable processes, both companies in the above examples could focus on other work and reduce the mental load and resource expenditure they would otherwise dedicate to monitoring file-heavy processes. 

The reason this worked out so well for this partnership is because the MFT solution went beyond automating simple tasks. Acme Scooters and Wheels Limited got full visibility into all file transfer processes, including comprehensive logging and reporting. Not only was it easier for their employees to check that a file transfer went through, but the integration with a WLA solution made tracking and reporting simple, from intake to storage. 

Your business transactions aren’t only taking place within your four walls. When you engage with external partners, you must meet compliance requirements, provide technical support when necessary and, most importantly, have peace of mind that all processes are working as intended. 

To be continued: What will your file transfer story look like?

If you’ve done the hard work of automating your organization’s essential tasks via a WLA platform, the next logical chapter in your journey is about bringing file transfers under the automation umbrella. 

Technology has come so far in the file transfer space, and a robust MFT solution like JSCAPE not only shepherds your files securely inside and outside your business but also helps you implement efficiencies in even the most complex job processes. 

If you aspire for your business to live and breathe in the cloud — a worthy and necessary aspiration in today’s landscape — modern WLA and MFT solutions should be at the top of your tech stack wish list. Redwood Software is the only provider offering SaaS for both. 

It’s time to automate your business inside and out. To avoid the negative impact of common assumptions in the process, download our list of 10 surprising but critical success factors for implementing end-to-end automation.

It’s worth remembering that “things”-as-code approaches originated from infrastructure-as-code (IaC) and the DevOps movement, which fundamentally changed infrastructure management and formed a foundation for business services and operations. 

During my time managing traditional and cloud infrastructures, I saw how instrumental this shift was in empowering IT teams to build, manage and scale cloud workloads. Although it’s not the panacea some hoped it would be, it is of huge value to teams today.

IaC took us from using disconnected scripts and manual activities to creating infrastructure configurations for networking and servers to being able to easily deploy and set up systems in just a few clicks or API calls.

However, where infrastructure automation is inherently technology-based — with the requirements, planning and execution handled by people with technical skill sets — job scheduling via workload automation (WLA), bridges the gap between IT and business use cases.

Making workload automation accessible

While you can achieve WLA with JaC, it’s also possible to develop organization-wide automations with far less time and resources on the IT side. 

Where traditional job scheduling is time-based and used for automating IT processes, advanced WLA offers a significantly wider set of capabilities to automate business processes across multiple work streams and applications.

Because WLA solutions automate both business and IT processes, they bridge the gap from infrastructure architecture to enterprise and business architecture. Therefore, business rules and logic are inherently a part of implementation.

In that context, the goal is to democratize automation to empower people cross-functionally, accelerating the impact of decision-making to build a more efficient enterprise.

It’s vital for business or hybrid business/technical users to be able to leverage the benefits of a JaC approach.

The power of the object-based model without jobs-as-code

When working in code, developers can build solutions to easily reuse parts of their code, standardizing common and repetitive tasks or configurations. The code must be structured enough for multiple use cases, portable and fit to handle problems well. 

One common way to achieve this is through object-oriented programming. (For my own safety, I should point out that this is not the only programming language that delivers reusability, but it is certainly the most popular.)

In the end, the effort to execute JaC is not always worth it, but there are parts of this method that present an opportunity. The best solutions borrow from multiple concepts, incorporating them to deliver efficient and accessible outcomes.

Let’s talk about how to achieve the same benefits as JaC without the heavy IT burden.

Standardization and reusability

Programming, or coding, is one of the most powerful tools in the computing arsenal. What you can achieve is only limited by the bounds of the computer system you are coding for. With that power comes complexity.

The components that make up the structure of a workflow are limited — we can list them. For example, complex scheduling rules based on business processes, time zones, prioritization and escalation rules.

Enterprise workload automation platforms can deliver these benefits in a user-friendly way, as long as they have strong templating features and globally reusable components that all users can leverage to build jobs, integrate third-party systems and perform common tasks.

With a JaC origin but aligned with business concepts, WLA platforms can ensure that components and workflows represent the ways enterprises deliver services and manage daily business operations.

Connectivity and extensibility

Reusability in code also enables us to connect systems and extend actions into other systems, such as extracting data from databases, controlling operating systems, talking to SaaS platforms — the list is endless.

In a WLA environment, this happens via native integrations and an extensible connector model, enhanced with custom scripting and direct control over third-party systems through agents and APIs.

This enhances accessibility and stability. When a platform natively manages these components, it inherently controls them.

Admittedly, in this model, you’ll likely need to employ code of some kind. For example, scripting could enable you to interact with a remote system using your programming language of choice.

Version control and collaboration

Release management is a critical part of taking anything from the design stage into production. Usually, there’s a three-tier environment: changes progress from development into testing and, finally, production. 

It’s important to meet dependencies across the three stages to achieve maximum confidence that the workload will operate successfully in production.

With a system made up of a specific set of components and configurations, in-product release management delivers the safest and most reliable method for WLA release management.

The result is essential visibility into a workflow’s design, configuration and dependencies.

Scalability and agility

Generally speaking, when writing code, there’s a lot to be said for agility. When you can fundamentally change how a component or configuration works very quickly, you can see the result of that quickly, too.

WLA requires that you perform many discrete— and often different — tasks, or jobs. By reusing job definitions and other objects and injecting custom data (or parameters) into individual jobs and the larger workflow, you can unlock scalability without sacrificing accessibility.

A more user-friendly and accessible approach to WLA also mitigates the scalability challenges that can result from placing control over resource usage and process design into a code-based approach.

Empower developers to do what they do best

Although code-based approaches deliver all of the benefits outlined above, consider whether they’re the best use of limited development resources. 

You may be able to attain the benefits of JaC without needing costly deep development skills. Developers are an invaluable resource, and JaC can place unnecessary demands on them.

A solution that allows you to use components at scale without understanding a programming language frees developers to work on more strategic projects and makes the most effective use of all available resources for the benefit of your business.

Build a less resource-heavy automation fabric

As automation continues to expand in importance to touch every corner of enterprise organizations, it’s unclear if JaC will be the answer to more effective workload and workflow automation. It will always be wise to find new, more efficient ways to achieve your desired results. 

An accessible WLA solution brings your entire organization together in the drive for seamless job orchestration. The right one connects your applications and systems, allows all types of users to build new automations quickly and gives you the control and confidence to stick to SLAs.

Discover how to achieve more with less using Redwood Software’s automation solutions. Book a quick demo today.

Given that more than 80% of global businesses are planning process automation initiatives, this moment in time is likely a crucial turning point in your business process automation journey. How should you go about developing and automating durable processes?

In this article, we’ll examine the process-related root causes of your less-than-optimal business outcomes and how to build a central nervous system in the form of end-to-end process automation that supports efficient growth.

What is an end-to-end business process?

To understand the difficulty of establishing a true end-to-end process, we should first align on what it is.

An end-to-end business process is a series of interconnected steps that collectively deliver a product or service. It encompasses all stages from initiation to completion and often requires coordination across multiple business units. 

Examples of end-to-end processes in various verticals

Processes look different for different business functions, but in every instance, an end-to-end process closes a cycle or loop that must repeat from beginning to end.

Consider some industry-specific examples:

• A utility company automatically monitors usage across a network of meters in real time and collects data in a central control system. The billing department converts usage data into invoices based on current rates and leverages billing software to distribute invoices to customers. Customer service representatives address disputes. The payment processing team follows up on overdue accounts while the finance team records successful payments.
• A retailer receives goods from suppliers, sorts them in its warehouse and prepares them for dispatch to various retail outlets or directly to consumers. Logistics teams, warehouse staff and POS systems track and optimize the flow of goods to ensure a positive customer experience.
• A consumer places an order online or with an electronics distributor. An order management system captures details and initiates production planning and manufacturing. It checks inventory for raw materials, then sets into motion assembly line operations, quality assurance tests and packaging. Logistics then coordinates delivery while a finance team creates an invoice and processes payment. When payment is received, the process loop closes.

Barriers to constructing end-to-end business processes

While their repetitive nature may make them seem simple to set up, end-to-end processes are constructed from many micro processes that must happen in just the right order at just the right time. Overwhelmed by a volume humans can’t handle, technology solutions that fail to speak to one another and siloed functions, many leaders resort to building processes that fall short of end-to-end. 

Human limitations

With any business process at scale, technology plays a starring role. Humans don’t have the time or capacity to complete as many tasks as are necessary to keep huge numbers of end-to-end processes flowing error-free. The sheer volume of data involved and the interconnectivity of modern enterprise systems require rapid decision-making and adaptation that outpace human reaction times. Bottlenecks are unavoidable and consistency is impossible when people are in charge beyond a certain critical growth stage.

Disjointed tech 

Many organizations also grapple with legacy technological architecture. Outdated systems and a proliferation of applications, including some with cumbersome customizations, can’t keep pace with the process automation evolution. Fragmentation via isolated solutions creates data silos, prevents holistic analysis and may necessitate custom coding when you’re ready to automate across the entire tech stack. Even if your leadership team recognizes the negative impact of compartmentalized information, they might be reluctant to invest the effort and resources necessary to update or replace old technology to make end-to-end automation successful.

Instead of having a solution that’s only meaningful to and accessible by your IT or operations team, for example, you need a fully integrated automation layer that transmits signals like a nervous system to every corner of your business.

Siloed visibility

The most common kink in an enterprise process nexus is this reluctance, amplified — It’s people, not infrastructure. In most roles, you won’t inherently be aware of what everyone else in the organization is doing. It’s normal to focus on your responsibilities and fail to see the bigger picture. However unintentional, this leads to the acceptance of inefficiency across many departments and processes. What you can’t see, you can’t fix.

How the day-to-day drives outcomes

End-to-end automation requires a mindset shift. Instead of zooming in on micro processes your team takes part in and staying in that myopic state, imagine them rolling up into macro processes that span multiple business functions. When macro processes become uninterrupted from beginning to end, your desired outcomes are within reach. See the chart below for how properly implemented automation supports seamless operations.

Implement your business’s nervous system

Your personal nervous system drives your ability to move, think and respond to your environment. It’s a network of impulses that manages input and output across all systems of your body. If you’ve developed sufficient coping skills, such as breathing techniques or static stretching, you can better handle what life throws your way.

Similarly, an automation nervous system must integrate and monitor all functions to ensure minor stressors don’t disrupt operations. In an environment where you’re carrying out huge numbers of repetitive tasks per day (10,000+), all of them must take place on time and factor in complex dependencies for your larger, goal-driven end-to-end processes to work. Orchestrating these tasks via comprehensive business process automation is the only viable solution.

Components of an automation-driven nervous system 

It’s not one person’s job to transition your business processes from disconnected and inefficient to unified and streamlined. It’s a strategic move by multiple process owners for the benefit of every stakeholder. To initiate and follow through on this change, your teams should be educated on the optimal infrastructure.

A well-functioning nervous system in business:

• is built on a tightly integrated foundation of enterprise-grade workload automation (WLA) and managed file transfer (MFT) solutions that support unencumbered mission-critical processes. 
• connects your tech stack via an intuitive integration layer that reduces the need for and risk of workarounds or vulnerable endpoints.
• enables IT to swiftly and smoothly collaborate with all departments to drive success and adoption among business users.
• supports the design and development of entire processes at any scale and for any industry.

Large-scale business process management via automation 

Automating critical business processes today is all about making it easier to design and develop those processes from end to end. With drag-and-drop interfaces, templates and automation wizards, you can strengthen your organization’s nervous system and establish resilience despite the volatility of the market  — or the world.

Collaboration between IT and other departments is critical to successful automation initiatives. Traditionally, there has been a divide between technical experts and business users. Bridging this gap ensures that automations properly align with strategic objectives. An effective automation platform enables non-technical users while delivering the power and flexibility that IT professionals require.

A solution that connects a hybrid tech stack sans programming and scales easily without additional technical staff or human capital investment empowers your business to evolve and accommodate future processes and technologies. 

Enterprise automation in practice: “No limits” for Journal Media Group

What does successful organization-wide automation look like? With RunMyJobs by Redwood, Journal Media Group knows from firsthand experience.

The company’s 35 radio stations, 13 TV stations and more than 20 newspapers and magazines across 11 US states keep its teams busy. In-house systems, multiple IT divisions and too many systems made it tough to confidently promise important business outcomes, such as delivering newspapers no later than 6 AM daily.

By migrating to cloud-based applications, eliminating manual steps and combining advertising, circulation and billing in one highly flexible environment, Journal Media Group discovered the benefits of a single solution. The business automated 30 in-house systems altogether. Data extraction and distribution are now complete by 5:30 PM each evening, allowing the team plenty of time to troubleshoot before morning delivery.

Achieve digital transformation and stay nimble with Redwood Software

Start building your organizational nervous system with a full stack advanced automation solution like RunMyJobs. Whether you choose an on-premise or cloud environment, RunMyJobs connects all your systems and data, provides end-to-end visibility and enables effortless automation creation. 
Discover the power of a modern automation fabric — a connective layer that integrates all of your essential processes and enables unprecedented growth and innovation. Book a demo of Redwood’s solutions to explore the potential impact on your business outcomes.

Redwood defines an automation fabric as an integrated system that seamlessly connects applications, processes and data, driving mission-critical business outcomes. An automation fabric acts as a central nervous system enabling seamless communication among disparate business activities, applications and environments driving mission-critical outcomes across any tech stack.

Jobs-as-code (JaC) help create and operate automation fabrics that are efficient, reliable, and adaptable. It treats automation workflows as code, bringing the benefits of version control, testing, and collaboration to the world of enterprise automation.

What is jobs-as-code (JaC)?

Traditionally, operations teams often siloed and managed automation tasks separate from development. Jobs-as-code breaks down these barriers by allowing automation logic to be defined in code and accessible in familiar programming languages in a developer’s IDE of choice. This code can then be stored in version control systems like Git, alongside the application code itself.

Jobs-as-code plays a crucial role in the development of automation fabrics.  Imagine an automation fabric as a flexible, interconnected network that automates various tasks across your IT infrastructure. JaC acts as the building blocks for this fabric, providing a standardized and code-driven approach to automation. 

How JaC contributes to automation fabrics

Standardization and reusability

• Because JaC defines automation tasks in a consistent manner using code, standardization is created across different automation needs, fostering the reusability of code components. These reusable components can then be easily integrated into various workflows within the automation fabric.

Interconnectivity

• JaC workflows can be triggered by events or outputs from other JaC workflows. This enables seamless communication and coordination between different automation tasks within the fabric. Imagine a data pipeline JaC workflow triggering an application deployment JaC workflow upon successful data processing.

Version control and collaboration

• By treating automation as code, JaC allows for version control and collaboration. This ensures all teams involved (development and operations) work with the same, well-defined automation logic. A collaborative approach is essential for building and maintaining a complex automation fabric.

Scalability and agility

• JaC workflows are easily scalable. As your automation needs grow, you can modify and expand existing JaC code to accommodate new tasks within the fabric. Additionally, JaC facilitates rapid changes to workflows through code updates, making the automation fabric more agile.

Benefits of JaC for automation fabrics

• Simplified fabric creation: JaC streamlines the development and deployment of automation fabrics by providing standardized building blocks.
  
• Improved reliability: Version control and testing capabilities of JaC lead to more reliable and predictable automation processes within the fabric.
  
• Enhanced maintainability: JaC code can be easily documented and maintained, making the overall automation fabric easier to manage and troubleshoot.

Redwood can help you leverage JaC in building/operating automation fabrics

With Redwood, developers can author jobs in their IDE environment, and use APIs to run and manage their automation fabrics. They can also streamline their CI/CD process by leveraging repository tools like Github to manage versioning and change control to roll out and keep on top of process changes. 

Conclusion

JaC serves as the foundation for building robust and efficient automation fabrics. By providing a standardized, code-driven approach to automation, JaC unlocks the full potential of automation fabrics, enabling enterprises to achieve a high degree of automation across their IT infrastructure. Redwood enables the use of JaC to build and maintain mission-critical, reliable automation fabrics.